Datasets:

DeepNLP
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ICRA-2021-Accepted-Papers

title stringlengths 26 165	detail_url stringlengths 45 45	author_list sequencelengths 2 36	abstract stringlengths 382 403
Uncertainty-aware Non-linear Model Predictive Control for Human-following Companion Robot	https://ieeexplore.ieee.org/document/9561974/	[ "Shunichi Sekiguchi", "Ayanori Yorozu", "Kazuhiro Kuno", "Masaki Okada", "Yutaka Watanabe", "Masaki Takahashi", "Shunichi Sekiguchi", "Ayanori Yorozu", "Kazuhiro Kuno", "Masaki Okada", "Yutaka Watanabe", "Masaki Takahashi" ]	For a companion robot that follows a person as an assistant, predicting human walking is important to produce a proactive movement that is helpful to maintain an appropriate area decided by the human personal space. However, fully trusting the prediction may result in obstructing human walking because it is not always accurate. Hence, we consider the estimation of uncertainty (i.e., entropy) of th...
Path Planning in Uncertain Ocean Currents using Ensemble Forecasts	https://ieeexplore.ieee.org/document/9561626/	[ "Chanyeol Yoo", "James Ju Heon Lee", "Stuart Anstee", "Robert Fitch", "Chanyeol Yoo", "James Ju Heon Lee", "Stuart Anstee", "Robert Fitch" ]	We present a path planning framework for marine robots subject to uncertain ocean currents that exploits data from ensemble forecasting, which is a technique for current prediction used in oceanography. Ensemble forecasts represent a distribution of predicted currents as a set of flow fields that are considered to be equally likely. We show that the typical approach of computing the vector-wise me...
Distributed Motion Coordination Using Convex Feasible Set Based Model Predictive Control	https://ieeexplore.ieee.org/document/9561637/	[ "Hongyu Zhou", "Changliu Liu", "Hongyu Zhou", "Changliu Liu" ]	The implementation of optimization-based motion coordination approaches in real world multi-agent systems remains challenging due to their high computational complexity and potential deadlocks. This paper presents a distributed model predictive control (MPC) approach based on convex feasible set (CFS) algorithm for multi-vehicle motion coordination in autonomous driving. By using CFS to convexify ...
Risk-Conditioned Distributional Soft Actor-Critic for Risk-Sensitive Navigation	https://ieeexplore.ieee.org/document/9560962/	[ "Jinyoung Choi", "Christopher Dance", "Jung-Eun Kim", "Seulbin Hwang", "Kyung-Sik Park", "Jinyoung Choi", "Christopher Dance", "Jung-Eun Kim", "Seulbin Hwang", "Kyung-Sik Park" ]	Modern navigation algorithms based on deep reinforcement learning (RL) show promising efficiency and robustness. However, most deep RL algorithms operate in a risk-neutral manner, making no special attempt to shield users from relatively rare but serious outcomes, even if such shielding might cause little loss of performance. Furthermore, such algorithms typically make no provisions to ensure safe...
Optimized Method for Planning and Controlling the Somersault Motion of Quadruped Robot	https://ieeexplore.ieee.org/document/9560903/	[ "Teng Chen", "Xuewen Rong", "Yibin Li", "Teng Chen", "Xuewen Rong", "Yibin Li" ]	A method for planning and controlling the somersault motion of a quadruped robot is proposed in this paper. The method divides the somersault motion into 5 stages according to intuitive understanding. Based on the simplified dynamic model, the linear programming method is used to obtain the maximum ground reaction force under the constraints of joint torque and friction cone, and then the optimal ...
Motion Coupling Analysis for the Decoupled Design of a Two-segment Notched Continuum Robot	https://ieeexplore.ieee.org/document/9561764/	[ "Wenhui Zeng", "Junyan Yan", "Xu Huang", "Shing Shin Cheng", "Wenhui Zeng", "Junyan Yan", "Xu Huang", "Shing Shin Cheng" ]	Multi-segment continuum robots, that offer inherent compliance and distal dexterity, are suitable for deployment in minimally invasive surgical procedures. Cable-driven mechanism is commonly used in continuum surgical robots but could lead to inter-segment motion coupling in a multi-segment robot. In this paper, we present a coupled mechanics model for a two-segment notched continuum robot to anal...
VINS-Motion: Tightly-coupled Fusion of VINS and Motion Constraint	https://ieeexplore.ieee.org/document/9562103/	[ "Zhelin Yu", "Lidong Zhu", "Guoyu Lu", "Zhelin Yu", "Lidong Zhu", "Guoyu Lu" ]	In this paper, we develop a novel visual-inertial navigation system with motion constraint (VINS-Motion), which extends the visual-inertial navigation system (VINS) to incorporate vehicle motion constraints for improving the autonomous vehicles localization accuracy. Besides the prior information, IMU measurement residual, and visual measurement residual utilized in VINS, vehicle orientation/veloc...
Robot-to-image Registration with Geometric Marker for CT-guided Robotic Needle Insertion	https://ieeexplore.ieee.org/document/9561876/	[ "Iori Ikeda", "Kai Sekine", "Ryosuke Tsumura", "Hiroyasu Iwata", "Iori Ikeda", "Kai Sekine", "Ryosuke Tsumura", "Hiroyasu Iwata" ]	A computed tomography (CT)-guided robotic needle requires registration to transfer coordinates between the robot and CT image for accurate insertion. In our previous work, we proposed a geometric marker that allows direct registration between a CT image and robot and demonstrated its proof of concept. In this paper, we present a registration algorithm for calculating the six-degrees-of-freedom err...
Shape Sensor Using Magnetic Induction with Frequency Sweeping for Medical Catheters	https://ieeexplore.ieee.org/document/9561072/	[ "Jiyun Jeon", "Chunwoo Kim", "Jiyun Jeon", "Chunwoo Kim" ]	Shape sensors are important for safer and more dexterous manipulation of the medical catheters. Among the electromagnetic based shape sensors, a voice coil shape sensor measures the variation of a mutual inductance between the coils placed along the tube due to the bending of the tube. Owing to the design flexibility of a voice coil, it offers the small size without the external magnetic field gen...
Temperature Compensated 3D Printed Strain Sensor for Advanced Manufacturing Applications	https://ieeexplore.ieee.org/document/9561498/	[ "Nuwan Munasinghe", "John Masangkay", "Gavin Paul", "Nuwan Munasinghe", "John Masangkay", "Gavin Paul" ]	Additive Manufacturing, has evolved beyond prototyping to manufacturing end-products. The authors are involved in developing a large-scale extrusion-based 3D printer to print mining equipment - a Gravity Separation Spiral, and embedding sensors to monitor the operational conditions re-motely. This paper presents a temperature-compensated strain sensor that can be 3D printed inline within large-sca...
Design of a deployable underwater robot for the recovery of autonomous underwater vehicles based on origami technique	https://ieeexplore.ieee.org/document/9561345/	[ "Jisen Li", "Yuliang Yang", "Yumei Zhang", "Hua Zhu", "Yongqi Li", "Qiujun Huang", "Haibo Lu", "Shan He", "Shengquan Li", "Wei Zhang", "Tao Mei", "Feng Wu", "Aidong Zhang", "Jisen Li", "Yuliang Yang", "Yumei Zhang", "Hua Zhu", "Yongqi Li", "Qiujun Huang", "Haibo Lu", "Shan He", "Shengquan Li", "Wei Zhang", "Tao Mei", "Feng Wu", "Aidong Zhang" ]	The recovery of autonomous underwater vehicles (AUVs) has been a challenging mission due to the limited localization accuracy and movement capability of the AUVs. To overcome these limitations, we propose a novel design of a deployable underwater robot (DUR) for the recovery mission. Utilizing the origami structure, the DUR can transform between open and closed states to maximize the performance a...
Modelling and optimisation of a mechanism-based metamaterial for a wrist flexion-extension assistive device	https://ieeexplore.ieee.org/document/9562099/	[ "Suhas Raghavendra Kulkarni", "Bernardo Noronha", "Domenico Campolo", "Dino Accoto", "Suhas Raghavendra Kulkarni", "Bernardo Noronha", "Domenico Campolo", "Dino Accoto" ]	In this paper we present a methodology for optimising the design of a metamaterial structure with one degree of freedom that is able to simultaneously bend and stretch. The structure is intended for assisting flexion-extension of the wrist joint. The metamaterial is comprised of serially connected, individually designed cells. The design parameters can be chosen to optimally fit a desired planar c...
Mechatronic Design of A Low-Noise Active Knee Prosthesis with High Backdrivability	https://ieeexplore.ieee.org/document/9562052/	[ "Guoxiang Fu", "Jinying Zhu", "Zilu Wang", "Jingeng Mai", "Qining Wang", "Guoxiang Fu", "Jinying Zhu", "Zilu Wang", "Jingeng Mai", "Qining Wang" ]	In this paper, we present a low-damping active knee prosthesis (LDKP) with low noise and high backdrivability. The proposed prosthesis is driven by a motor and then decelerated by a four-stage synchronous belt. High backdrivability given by this structure accelerates the prosthetic response. A control system containing several sensors are embedded in the proposed prosthesis to recognize different ...
Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery	https://ieeexplore.ieee.org/document/9561749/	[ "Chia-Man Hung", "Li Sun", "Yizhe Wu", "Ioannis Havoutis", "Ingmar Posner", "Chia-Man Hung", "Li Sun", "Yizhe Wu", "Ioannis Havoutis", "Ingmar Posner" ]	End-to-end visuomotor control is emerging as a compelling solution for robot manipulation tasks. However, imitation learning-based visuomotor control approaches tend to suffer from a common limitation, lacking the ability to recover from an out-of-distribution state caused by compounding errors. In this paper, instead of using tactile feedback or explicitly detecting the failure through vision, we...
Sim-to-Real Visual Grasping via State Representation Learning Based on Combining Pixel-Level and Feature-Level Domain Adaptation	https://ieeexplore.ieee.org/document/9561302/	[ "Youngbin Park", "Sang Hyoung Lee", "Il Hong Suh", "Youngbin Park", "Sang Hyoung Lee", "Il Hong Suh" ]	In this study, we present a method to grasp diverse unseen real-world objects using an off-policy actor-critic deep reinforcement learning (RL) with the help of a simulation and the use of as little real-world data as possible. Actor-critic deep RL is unstable and difficult to tune when a raw image is given as an input. Therefore, we use state representation learning (SRL) to make actor-critic RL ...
Dexterous Manoeuvre through Touch in a Cluttered Scene	https://ieeexplore.ieee.org/document/9562061/	[ "Wenyu Liang", "Qinyuan Ren", "Xiaoqiao Chen", "Junli Gao", "Yan Wu", "Wenyu Liang", "Qinyuan Ren", "Xiaoqiao Chen", "Junli Gao", "Yan Wu" ]	Manipulation in a densely cluttered environment creates complex challenges in perception to close the control loop, many of which are due to the sophisticated physical interaction between the environment and the manipulator. Drawing from biological sensory-motor control, to handle the task in such a scenario, tactile sensing can be used to provide an additional dimension of the rich contact inform...
Mapless-Planner: A Robust and Fast Planning Framework for Aggressive Autonomous Flight without Map Fusion	https://ieeexplore.ieee.org/document/9561460/	[ "Jialin Ji", "Zhepei Wang", "Yingjian Wang", "Chao Xu", "Fei Gao", "Jialin Ji", "Zhepei Wang", "Yingjian Wang", "Chao Xu", "Fei Gao" ]	Maintaining a map online is resource-consuming while a robust navigation system usually needs environment abstraction via a well-fused map. In this paper, we propose a mapless local planner which directly conducts such abstraction on the unfused sensor data. A limited-memory data structure with a reliable proximity query algorithm is proposed for maintaining raw historical information. A sampling-...
Robotic Indoor Scene Captioning from Streaming Video	https://ieeexplore.ieee.org/document/9560904/	[ "Xinghang Li", "Di Guo", "Huaping Liu", "Fuchun Sun", "Xinghang Li", "Di Guo", "Huaping Liu", "Fuchun Sun" ]	Robots are usually equipped with cameras to explore the indoor scene and it is expected that the robot can well describe the scene with natural language. Although some great success has been achieved in image and video captioning technology, especially on many public datasets, the caption generated from indoor scene video is still not informative and coherent enough. In this paper, we propose the ...
Geometry-Aware Unsupervised Domain Adaptation for Stereo Matching	https://ieeexplore.ieee.org/document/9561628/	[ "Hiroki Sakuma", "Yoshinori Konishi", "Hiroki Sakuma", "Yoshinori Konishi" ]	Recently proposed DNN-based stereo matching methods that learn priors directly from data are known to suffer a drastic drop in accuracy in new environments. Although supervised approaches with ground truth disparity maps often work well, collecting them in each deployment environment is cumbersome and costly. For this reason, many unsupervised domain adaptation methods based on image-to-image tran...
Reasoning Operational Decisions for Robots via Time Series Causal Inference	https://ieeexplore.ieee.org/document/9561659/	[ "Yu Cao", "Boyang Li", "Qian Li", "Adam Stokes", "David Ingram", "Aristides Kiprakis", "Yu Cao", "Boyang Li", "Qian Li", "Adam Stokes", "David Ingram", "Aristides Kiprakis" ]	Justifying operational decisions for robots is a challenging task as the operator or the robot itself has to understand the underlying physical interaction between the robot and the environment to predict the potential outcome. It is desirable to understand how the decision influences the operational performance in the way of causal relationship for the purpose of explainable decision-making. Here...
HueCode: A Meta-marker Exposing Relative Pose and Additional Information in Different Colored Layers	https://ieeexplore.ieee.org/document/9561783/	[ "Yoshito Okada", "Daiki Fujikura", "Yu Ozawa", "Kenjiro Tadakuma", "Kazunori Ohno", "Satoshi Tadokoro", "Yoshito Okada", "Daiki Fujikura", "Yu Ozawa", "Kenjiro Tadakuma", "Kazunori Ohno", "Satoshi Tadokoro" ]	In this paper, HueCode, a meta-marker that robustly and simultaneously exposes the relative pose between a marker and a camera along with additional information, is proposed. It occupies the area of a single marker by overlaying multiple types of markers in different colored layers. Using perspective information from the first (most recognizable) type of element marker, the second or higher marker...
B-splines for Purely Vision-based Localization and Mapping on Non-holonomic Ground Vehicles	https://ieeexplore.ieee.org/document/9561131/	[ "Kun Huang", "Yifu Wang", "Laurent Kneip", "Kun Huang", "Yifu Wang", "Laurent Kneip" ]	Purely vision-based localization and mapping is a cost-effective and thus attractive solution to localization and mapping on smart ground vehicles. However, the accuracy and especially robustness of vision-only solutions remain rivalled by more expensive, lidar-based multi-sensor alternatives. We show that a significant increase in robustness can be achieved if taking non-holonomic kinematic const...
Robust SRIF-based LiDAR-IMU Localization for Autonomous Vehicles	https://ieeexplore.ieee.org/document/9561218/	[ "Kun Li", "Zhanpeng Ouyang", "Lan Hu", "Dayang Hao", "Laurent Kneip", "Kun Li", "Zhanpeng Ouyang", "Lan Hu", "Dayang Hao", "Laurent Kneip" ]	We present a tightly-coupled multi-sensor fusion architecture for autonomous vehicle applications, which achieves centimetre-level accuracy and high robustness in various scenarios. In order to realize robust and accurate point-cloud feature matching we propose a novel method for extracting structural, highly discriminative features from LiDAR point clouds. For high frequency motion prediction and...
Structure Reconstruction Using Ray-Point-Ray Features: Representation and Camera Pose Estimation	https://ieeexplore.ieee.org/document/9561283/	[ "Yijia He", "Xiangyue Liu", "Xiao Liu", "Ji Zhao", "Yijia He", "Xiangyue Liu", "Xiao Liu", "Ji Zhao" ]	Straight line features have been increasingly utilized in visual SLAM and 3D reconstruction systems. The straight lines’ parameterization, parallel constraint, and coplanar constraint are studied in many recent works. In this paper, we explore the novel intersection constraint of straight lines for structure reconstruction. First, a minimum parameterized representation of ray-point-ray (RPR) struc...
Reducing the Deployment-Time Inference Control Costs of Deep Reinforcement Learning Agents via an Asymmetric Architecture	https://ieeexplore.ieee.org/document/9562026/	[ "Chin-Jui Chang", "Yu-Wei Chu", "Chao-Hsien Ting", "Hao-Kang Liu", "Zhang-Wei Hong", "Chun-Yi Lee", "Chin-Jui Chang", "Yu-Wei Chu", "Chao-Hsien Ting", "Hao-Kang Liu", "Zhang-Wei Hong", "Chun-Yi Lee" ]	Deep reinforcement learning (DRL) has been demonstrated to provide promising results in several challenging decision making and control tasks. However, the required inference costs of deep neural networks (DNNs) could prevent DRL from being applied to mobile robots which cannot afford high energy-consuming computations. To enable DRL methods to be affordable in such energy-limited platforms, we pr...
Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation	https://ieeexplore.ieee.org/document/9561842/	[ "Yao Yao", "Li Xiao", "Zhicheng An", "Wanpeng Zhang", "Dijun Luo", "Yao Yao", "Li Xiao", "Zhicheng An", "Wanpeng Zhang", "Dijun Luo" ]	Model-based deep reinforcement learning has achieved success in various domains that require high sample efficiencies, such as Go and robotics. However, there are some remaining issues, such as planning efficient explorations to learn more accurate dynamic models, evaluating the uncertainty of the learned models, and more rational utilization of models. To mitigate these issues, we present MEEE, a...
Dreaming: Model-based Reinforcement Learning by Latent Imagination without Reconstruction	https://ieeexplore.ieee.org/document/9560734/	[ "Masashi Okada", "Tadahiro Taniguchi", "Masashi Okada", "Tadahiro Taniguchi" ]	In the present paper, we propose a decoder-free extension of Dreamer, a leading model-based reinforcement learning (MBRL) method from pixels. Dreamer is a sample- and cost-efficient solution to robot learning, as it is used to train latent state-space models based on a variational autoencoder and to conduct policy optimization by latent trajectory imagination. However, this autoencoding based appr...
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning	https://ieeexplore.ieee.org/document/9560832/	[ "Hany Abdulsamad", "Peter Nickl", "Pascal Klink", "Jan Peters", "Hany Abdulsamad", "Peter Nickl", "Pascal Klink", "Jan Peters" ]	Probabilistic regression techniques in control and robotics applications have to fulfill different criteria of data-driven adaptability, computational efficiency, scalability to high dimensions, and the capacity to deal with different modalities in the data. Classical regressors usually fulfill only a subset of these properties. In this work, we extend seminal work on Bayesian nonparametric mixtur...
Model-based Domain Randomization of Dynamics System with Deep Bayesian Locally Linear Embedding	https://ieeexplore.ieee.org/document/9561942/	[ "J. Hyeon Park", "Sungyong Park", "H. Jin Kim", "J. Hyeon Park", "Sungyong Park", "H. Jin Kim" ]	Domain randomization (DR) is a powerful tool to make a policy robust to the uncertainty of dynamics caused by unobservable environmental parameters. Conventional DR has adopted model-free reinforcement learning as a policy optimizer. However, the model-free methods in DR demand high time-complexity due to the randomization process where the environment is extremely changed. In this paper, we intro...
Deep Imitation Learning for Autonomous Navigation in Dynamic Pedestrian Environments	https://ieeexplore.ieee.org/document/9561220/	[ "Lei Qin", "Zefan Huang", "Chen Zhang", "Hongliang Guo", "Marcelo Ang", "Daniela Rus", "Lei Qin", "Zefan Huang", "Chen Zhang", "Hongliang Guo", "Marcelo Ang", "Daniela Rus" ]	Navigation through dynamic pedestrian environments in a socially compliant manner is still a challenging task for autonomous vehicles. Classical methods usually lead to unnatural vehicle behaviours for pedestrian navigation due to the difficulty in modeling social conventions mathematically. This paper presents an end-to-end path planning system that achieves autonomous navigation in dynamic envir...
Learning from Demonstration without Demonstrations	https://ieeexplore.ieee.org/document/9561119/	[ "Tom Blau", "Philippe Morere", "Gilad Francis", "Tom Blau", "Philippe Morere", "Gilad Francis" ]	State-of-the-art reinforcement learning (RL) algorithms suffer from high sample complexity, particularly in the sparse reward case. A popular strategy for mitigating this problem is to learn control policies by imitating a set of expert demonstrations. The drawback of such approaches is that an expert needs to produce demonstrations, which may be costly in practice. To address this shortcoming, we...
Reachability-based Push Recovery for Humanoid Robots with Variable-Height Inverted Pendulum	https://ieeexplore.ieee.org/document/9561872/	[ "Shunpeng Yang", "Hua Chen", "Luyao Zhang", "Zhefeng Cao", "Patrick M. Wensing", "Yizhang Liu", "Jianxin Pang", "Wei Zhang", "Shunpeng Yang", "Hua Chen", "Luyao Zhang", "Zhefeng Cao", "Patrick M. Wensing", "Yizhang Liu", "Jianxin Pang", "Wei Zhang" ]	This paper studies push recovery for humanoid robots based on a variable-height inverted pendulum (VHIP) model. We first develop an approach for treating zero-step capturability of the VHIP with a novel methodology based on Hamilton-Jacobi (HJ) reachability analysis. Such an approach uses the sub-zero level set of a value function to encode capturability of the VHIP, where the value function is ob...
Meaningful Centroidal Frame Orientation of Multi-body Floating Locomotion Systems	https://ieeexplore.ieee.org/document/9560918/	[ "Wenqian Du", "Ze Wang", "Etienne Moullet", "Faïz Benamar", "Wenqian Du", "Ze Wang", "Etienne Moullet", "Faïz Benamar" ]	In this paper, we propose a meaningful definition of rotational centroidal orientation which is somewhat missed in the state-of-the-art centroidal momentum and dynamics theory for locomotion robots with one floating base. This centroidal instantaneous orientation rotates as the robot runs, and it is extracted from the total system angular inertia. The new centroidal frame is proposed to be paralle...
Soft-Jig-Driven Assembly Operations	https://ieeexplore.ieee.org/document/9562008/	[ "Takuya Kiyokawa", "Tatsuya Sakuma", "Jun Takamatsu", "Tsukasa Ogasawara", "Takuya Kiyokawa", "Tatsuya Sakuma", "Jun Takamatsu", "Tsukasa Ogasawara" ]	To design a general-purpose assembly robot system that can handle objects of various shapes, we propose a soft jig that fits to the shapes of assembly parts. The functionality of the soft jig is based on a jamming gripper developed in the field of soft robotics. The soft jig has a bag covered with a malleable silicone membrane, which has high friction, elongation, and contraction rates for keeping...
Prediction-Error Negativity to Assess Singularity Avoidance Strategies in Physical Human-Robot Collaboration	https://ieeexplore.ieee.org/document/9561599/	[ "Stefano Aldini", "Avinash K. Singh", "Marc Carmichael", "Yu-Kai Wang", "Dikai Liu", "Chin-Teng Lin", "Stefano Aldini", "Avinash K. Singh", "Marc Carmichael", "Yu-Kai Wang", "Dikai Liu", "Chin-Teng Lin" ]	In physical human-robot collaboration (pHRC), singularity avoidance strategies are often critical to obtain stable interaction dynamics. It is hypothesised a predictable singularity avoidance strategy is preferred in pHRC as humans tend to maximise predictability when using complex systems. By using an electroencephalogram (EEG), it is possible to assess the predictability of a task through a feat...
A Large Area Robotic Skin with Sparsely Embedded Microphones for Human-Robot Tactile Communication	https://ieeexplore.ieee.org/document/9561898/	[ "Min Jin Yang", "Kyungseo Park", "Jung Kim", "Min Jin Yang", "Kyungseo Park", "Jung Kim" ]	A human can socially interact in a non-verbal manner by understanding the intention behind a tactile stimulus. Patting on one’s back is one of tactile communications, which is considered as a sign of encouragement in most cultures. The majority of such tactile communication is carried out by a dynamic tactile on large passive body parts and differently interpreted by how and where on the body is t...
Star Topology based Interaction for Robust Trajectory Forecasting in Dynamic Scene	https://ieeexplore.ieee.org/document/9561067/	[ "Yanliang Zhu", "Dongchun Ren", "Deheng Qian", "Mingyu Fan", "Xin Li", "Huaxia Xia", "Yanliang Zhu", "Dongchun Ren", "Deheng Qian", "Mingyu Fan", "Xin Li", "Huaxia Xia" ]	Motion prediction of multiple agents in a dynamic scene is a crucial component in many real applications, including intelligent monitoring and autonomous driving. Due to the complex interactions among the agents and their interactions with the surrounding scene, accurate trajectory prediction is still a great challenge. In this paper, we propose a new method for robust trajectory prediction of mul...
A Peg-in-hole Task Strategy for Holes in Concrete	https://ieeexplore.ieee.org/document/9561370/	[ "André Yuji Yasutomi", "Hiroki Mori", "Tetsuya Ogata", "André Yuji Yasutomi", "Hiroki Mori", "Tetsuya Ogata" ]	A method that enables an industrial robot to accomplish the peg-in-hole task for holes in concrete is proposed. The proposed method involves slightly detaching the peg from the wall, when moving between search positions, to avoid the negative influence of the concrete’s high friction coefficient. It uses a deep neural network (DNN), trained via reinforcement learning, to effectively find holes wit...
TaskNet: A Neural Task Planner for Autonomous Excavator	https://ieeexplore.ieee.org/document/9561629/	[ "Jinxin Zhao", "Liangjun Zhang", "Jinxin Zhao", "Liangjun Zhang" ]	We present a novel task planner - TaskNet for an autonomous excavator based on a data-driven method, which plans feasible task-level sequence by learning from demonstration data. Given a high-level excavation objective, our TaskNet planner can decompose it into sub-tasks, each of which can be further decomposed into task primitives with specifications. We train our TaskNet using an excavation trac...
Steering Induced Roll Quantification During Ship Turning Circle Manoeuvre	https://ieeexplore.ieee.org/document/9560998/	[ "Nathanael Esnault", "Nitish Patel", "Jon Tunnicliffe", "Nathanael Esnault", "Nitish Patel", "Jon Tunnicliffe" ]	A well known and well-studied feature of boats’ dynamic is the effect of steering-induced roll. This property is used by a technique called Rudder Roll Stabilization (RRS) to stabilise ships in waves in order to make the navigation safer and more pleasant. This technique is based on the generation of induced roll. Because of its specific application, studies have been limited to commercial vessels...
Uncertainty-aware Self-supervised Target-mass Grasping of Granular Foods	https://ieeexplore.ieee.org/document/9561728/	[ "Kuniyuki Takahashi", "Wilson Ko", "Avinash Ummadisingu", "Shin-ichi Maeda", "Kuniyuki Takahashi", "Wilson Ko", "Avinash Ummadisingu", "Shin-ichi Maeda" ]	Food packing industry workers typically pick a target amount of food by hand from a food tray and place them in containers. Since menus are diverse and change frequently, robots must adapt and learn to handle new foods in a short time-span. Learning to grasp a specific amount of granular food requires a large training dataset, which is challenging to collect reasonably quickly. In this study, we p...
SCT-CNN: A Spatio-Channel-Temporal Attention CNN for Grasp Stability Prediction	https://ieeexplore.ieee.org/document/9561397/	[ "Gang Yan", "Alexander Schmitz", "Satoshi Funabashi", "Sophon Somlor", "Tito Pradhono Tomo", "Shigeki Sugano", "Gang Yan", "Alexander Schmitz", "Satoshi Funabashi", "Sophon Somlor", "Tito Pradhono Tomo", "Shigeki Sugano" ]	Recently, tactile sensing has attracted great interest for robotic manipulation. Predicting if a grasp will be stable or not, i.e. if the grasped object will drop out of the gripper while being lifted, can aid robust robotic grasping. Previous methods paid equal attention to all regions of the tactile data matrix or all time-steps in the tactile sequence, which may include irrelevant or redundant ...
Spherical Magnetic Joint for Inverted Locomotion of Multi-Legged Robot	https://ieeexplore.ieee.org/document/9561838/	[ "Harn Sison", "Photchara Ratsamee", "Manabu Higashida", "Tomohiro Mashita", "Yuki Uranishi", "Haruo Takemura", "Harn Sison", "Photchara Ratsamee", "Manabu Higashida", "Tomohiro Mashita", "Yuki Uranishi", "Haruo Takemura" ]	In this paper, we present a spherical magnetic joint for the inverted locomotion of a multi-legged robot. The permanent magnet’s spherical shape allows the robot to attach its foot to a steel surface without energy consumption. However, the robot’s inverted locomotion requires foot flexibility for placement and gait construction of the robot. Therefore, the spherical magnetic joint mechanism was d...
An Open-Source Mechanical Design of ALARIS Hand: A 6-DOF Anthropomorphic Robotic Hand	https://ieeexplore.ieee.org/document/9561977/	[ "Ayaulym Nurpeissova", "Talgat Tursynbekov", "Almas Shintemirov", "Ayaulym Nurpeissova", "Talgat Tursynbekov", "Almas Shintemirov" ]	This paper presents a new open-source mechanical design of a 6-DOF anthropomorphic ALARIS robotic hand that can serve as a low-cost design platform for further customization and utilization for research and educational purposes. The presented hand design employs linkage-based three-phalange finger and two-phalange adaptive thumb designs with non-backdrivable worm-and-rack transmission mechanisms. ...
Biomimetic Operational Space Control for Musculoskeletal Humanoid Optimizing Across Muscle Activation and Joint Nullspace	https://ieeexplore.ieee.org/document/9561919/	[ "Yasunori Toshimitsu", "Kento Kawaharazuka", "Manabu Nishiura", "Yuya Koga", "Yusuke Omura", "Yuki Asano", "Kei Okada", "Koji Kawasaki", "Masayuki Inaba", "Yasunori Toshimitsu", "Kento Kawaharazuka", "Manabu Nishiura", "Yuya Koga", "Yusuke Omura", "Yuki Asano", "Kei Okada", "Koji Kawasaki", "Masayuki Inaba" ]	We have implemented a force-based operational space controller on a physical musculoskeletal humanoid robot arm. The controller calculates muscle activations based on a biomimetic Hill-type muscle model. We propose a method to include the joint torque nullspace in the optimization process, which enables the robot to exploit the nullspace to gradually lower its overall muscle activation. We have ve...
Parallel Actuation of Nanorod Swarm and Nanoparticle Swarm to Different Targets	https://ieeexplore.ieee.org/document/9561625/	[ "Xingzhou Du", "Dongdong Jin", "Qianqian Wang", "Shihao Yang", "Philip Wai Yan Chiu", "Li Zhang", "Xingzhou Du", "Dongdong Jin", "Qianqian Wang", "Shihao Yang", "Philip Wai Yan Chiu", "Li Zhang" ]	After years of development, various swarms of robots have been proposed for many complicated tasks, such as forming patterns, cooperative locomotion, and adapting to different environments. However, controlling microrobotic swarms is still a challenging task owing to the lacking of integrated devices on the small-scale agents, and actuation of multiple microrobotic swarms to different targets unde...
Robotic Micromanipulation for Active Pin Alignment in Electronic Soldering Industry	https://ieeexplore.ieee.org/document/9561698/	[ "Hao Ren", "Xinyu Wu", "Wanfeng Shang", "Hao Ren", "Xinyu Wu", "Wanfeng Shang" ]	In the context of robotic high-precision soldering, we propose an image-based pin alignment control method based on active plastic deformation. The plastic deformation is a well-known failure mechanism in most situations, which includes a phenomenon that the objects do not return original state. Here, in contrast to this convention, we utilize the plastic deformation of the metal pin to do pin ali...
Observation Space Matters: Benchmark and Optimization Algorithm	https://ieeexplore.ieee.org/document/9561019/	[ "Joanne Taery Kim", "Sehoon Ha", "Joanne Taery Kim", "Sehoon Ha" ]	Recent advances in deep reinforcement learning (deep RL) enable researchers to solve challenging control problems, from simulated environments to real-world robotic tasks. However, deep RL algorithms are known to be sensitive to the problem formulation, including observation spaces, action spaces, and reward functions. There exist numerous choices for observation spaces but they are often designed...
Interleaving Fast and Slow Decision Making	https://ieeexplore.ieee.org/document/9561562/	[ "Aditya Gulati", "Sarthak Soni", "Shrisha Rao", "Aditya Gulati", "Sarthak Soni", "Shrisha Rao" ]	The "Thinking, Fast and Slow" paradigm of Kahneman proposes that we use two different styles of thinking—a fast and intuitive System 1 for certain tasks, along with a slower but more analytical System 2 for others. While the idea of using this two-system style of thinking is gaining popularity in AI and robotics, our work considers how to interleave the two styles of decision-making, i.e., how Sys...
Multi-output Infinite Horizon Gaussian Processes	https://ieeexplore.ieee.org/document/9561031/	[ "Jaehyun Lim", "Jehyun Park", "Sungjae Nah", "Jongeun Choi", "Jaehyun Lim", "Jehyun Park", "Sungjae Nah", "Jongeun Choi" ]	Learning the uncertain dynamical environments for online learning and prediction from noisy sensory measurement streams is essential for various tasks in robotics. Recently, Gaussian process (GP) online learning such as an infinite-horizon Gaussian process (IHGP) has shown effectiveness to cope with non-stationary dynamical random processes in learning hyperparameters online by reducing the comput...
Estimation and Adaption of Indoor Ego Airflow Disturbance with Application to Quadrotor Trajectory Planning	https://ieeexplore.ieee.org/document/9561679/	[ "Luqi Wang", "Boyu Zhou", "Chuhao Liu", "Shaojie Shen", "Luqi Wang", "Boyu Zhou", "Chuhao Liu", "Shaojie Shen" ]	It is ubiquitously accepted that during the autonomous navigation of the quadrotors, one of the most widely adopted unmanned aerial vehicles (UAVs), safety always has the highest priority. However, it is observed that the ego airflow disturbance can be a significant adverse factor during flights, causing potential safety issues, especially in narrow and confined indoor environments. Therefore, we ...
Real-time active detection of targets and path planning using UAVs	https://ieeexplore.ieee.org/document/9561365/	[ "Fangping Chen", "Yuheng Lu", "Yunyi Li", "Xiaodong Xie", "Fangping Chen", "Yuheng Lu", "Yunyi Li", "Xiaodong Xie" ]	This article proposes a new method that enables Unmanned Aerial Vehicles (UAVs) to actively find targets and shoot photographs of them in an unknown environment, while successfully avoiding surrounding obstacles and planning optimize routes. Owing to the limited computing ability on the UAVs, we obtained the point cloud data of surrounding objects, and selected the best segmentation method of the ...
EVA-Planner: Environmental Adaptive Quadrotor Planning	https://ieeexplore.ieee.org/document/9561759/	[ "Lun Quan", "Zhiwei Zhang", "Xingguang Zhong", "Chao Xu", "Fei Gao", "Lun Quan", "Zhiwei Zhang", "Xingguang Zhong", "Chao Xu", "Fei Gao" ]	The quadrotor is popularly used in challenging environments due to its superior agility and flexibility. In these scenarios, trajectory planning plays a vital role in generating safe motions to avoid obstacles while ensuring flight smoothness. Although many works on quadrotor planning have been proposed, a research gap exists in incorporating self-adaptation into a planning framework to enable a d...
Differential Information Aided 3-D Registration for Accurate Navigation and Scene Reconstruction	https://ieeexplore.ieee.org/document/9560754/	[ "Jin Wu", "Shuyang Zhang", "Yilong Zhu", "Ruoyu Geng", "Zhongtao Fu", "Fulong Ma", "Ming Liu", "Jin Wu", "Shuyang Zhang", "Yilong Zhu", "Ruoyu Geng", "Zhongtao Fu", "Fulong Ma", "Ming Liu" ]	A novel 3-dimensional (3-D) alignment method for point-cloud registration is proposed where the time-differential information of the measured points is employed. The new problem turns out to be a novel multi-dimensional optimization. Analytical solution to this optimization is then obtained, which sets the ground of further correspondence matching using k-D trees. Finally, via many examples, we sh...
Autonomous Navigation in Dynamic Environments with Multi-Modal Perception Uncertainties	https://ieeexplore.ieee.org/document/9561965/	[ "Hongliang Guo", "Zefan Huang", "Qiheng Ho", "Marcelo Ang", "Daniela Rus", "Hongliang Guo", "Zefan Huang", "Qiheng Ho", "Marcelo Ang", "Daniela Rus" ]	This paper addresses the safe path planning problem for autonomous mobility with multi-modal perception uncertainties. Specifically, we assume that different sensor inputs lead to different Gaussian process regulated perception uncertainties (named as multi-modal perception uncertainties). We implement a Bayesian inference algorithm, which merges the multi-modal GP-regulated uncertainties into a u...
Learning World Transition Model for Socially Aware Robot Navigation	https://ieeexplore.ieee.org/document/9561973/	[ "Yuxiang Cui", "Haodong Zhang", "Yue Wang", "Rong Xiong", "Yuxiang Cui", "Haodong Zhang", "Yue Wang", "Rong Xiong" ]	Moving in dynamic pedestrian environments is one of the important requirements for autonomous mobile robots. We present a model-based reinforcement learning approach for robots to navigate through crowded environments. The navigation policy is trained with both real interaction data from multi-agent simulation and virtual data from a deep transition model that predicts the evolution of surrounding...
Probabilistic Dynamic Crowd Prediction for Social Navigation	https://ieeexplore.ieee.org/document/9561053/	[ "Stefan H. Kiss", "Kavindie Katuwandeniya", "Alen Alempijevic", "Teresa Vidal-Calleja", "Stefan H. Kiss", "Kavindie Katuwandeniya", "Alen Alempijevic", "Teresa Vidal-Calleja" ]	In this paper, we present a novel approach that predicts spatially and temporally crowd behaviour for robotic social navigation. Integrating mobile robots into human society involves the fundamental problem of navigation in crowds. A robot should attempt to navigate in a way that is minimally invasive to the humans in its environment. However, planning in a dynamic environment is difficult as the ...
Consensus-Based Control Barrier Function for Swarm	https://ieeexplore.ieee.org/document/9561971/	[ "Manao Machida", "Masumi Ichien", "Manao Machida", "Masumi Ichien" ]	In swarm control, many robots coordinate their actions in a distributed and decentralized way. We propose a consensus-based control barrier function (CCBF) for a swarm. CCBF restricts the states of the whole distributed system, not just those of the individual robots. The barrier function is approximated by a consensus filter. We prove that CCBF constrains the control inputs for holding the forwar...
Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies	https://ieeexplore.ieee.org/document/9561573/	[ "Hanbit Oh", "Hikaru Sasaki", "Brendan Michael", "Takamitsu Matsubara", "Hanbit Oh", "Hikaru Sasaki", "Brendan Michael", "Takamitsu Matsubara" ]	Scenarios requiring humans to choose from multiple seemingly optimal actions are commonplace, however standard imitation learning often fails to capture this behavior. Instead, an over-reliance on replicating expert actions induces inflexible and unstable policies, leading to poor generalizability in an application. To address the problem, this paper presents the first imitation learning framework...
Active Modular Environment for Robot Navigation	https://ieeexplore.ieee.org/document/9561111/	[ "Shota Kameyama", "Keisuke Okumura", "Yasumasa Tamura", "Xavier Défago", "Shota Kameyama", "Keisuke Okumura", "Yasumasa Tamura", "Xavier Défago" ]	This paper presents a novel robot-environment interaction in navigation tasks such that robots have neither a representation of their working space nor planning function, instead, an active environment takes charge of these aspects. This is realized by spatially deploying computing units, called cells, and making cells manage traffic in their respective physical region. Different from stigmegic ap...
Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport	https://ieeexplore.ieee.org/document/9561274/	[ "Kazuki Shibata", "Tomohiko Jimbo", "Takamitsu Matsubara", "Kazuki Shibata", "Tomohiko Jimbo", "Takamitsu Matsubara" ]	In this paper, we explore a multi-agent reinforcement learning approach to address the design problem of communication and control strategies for multi-agent cooperative transport. Typical end-to-end deep neural network policies may be insufficient for covering communication and control; these methods cannot decide the timing of communication and can only work with fixed-rate communications. There...
Multi-Robot Task Allocation Games in Dynamically Changing Environments	https://ieeexplore.ieee.org/document/9561809/	[ "Shinkyu Park", "Yaofeng Desmond Zhong", "Naomi Ehrich Leonard", "Shinkyu Park", "Yaofeng Desmond Zhong", "Naomi Ehrich Leonard" ]	We propose a game-theoretic multi-robot task allocation framework that enables a large team of robots to optimally allocate tasks in dynamically changing environments. As our main contribution, we design a decision-making algorithm that defines how the robots select tasks to perform and how they repeatedly revise their task selections in response to changes in the environment. Our convergence anal...
An Upper Confidence Bound for Simultaneous Exploration and Exploitation in Heterogeneous Multi-Robot Systems	https://ieeexplore.ieee.org/document/9560822/	[ "Ki Myung Brian Lee", "Felix Kong", "Ricardo Cannizzaro", "Jennifer L. Palmer", "David Johnson", "Chanyeol Yoo", "Robert Fitch", "Ki Myung Brian Lee", "Felix Kong", "Ricardo Cannizzaro", "Jennifer L. Palmer", "David Johnson", "Chanyeol Yoo", "Robert Fitch" ]	Heterogeneous multi-robot systems are advantageous for operations in unknown environments because functionally specialised robots can gather environmental information, while others perform tasks. We de ne this decomposition as the scout–task robot architecture and show how it avoids the need to explicitly balance exploration and exploitation by permitting the system to do both simultaneously. The ...
Priority Patrolling using Multiple Agents	https://ieeexplore.ieee.org/document/9561785/	[ "Deepak Mallya", "Sumanth Kandala", "Leena Vachhani", "Arpita Sinha", "Deepak Mallya", "Sumanth Kandala", "Leena Vachhani", "Arpita Sinha" ]	The Patrolling Problem is a crucial feature of the surveillance task in defense and other establishments. Most of the works in the literature concentrate on reducing the Idleness value at each location in the environment. However, there are often a few prioritized locations that cannot be left unvisited beyond a certain Time Period. In this paper, we study the problem of Prioritized patrolling - t...
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements	https://ieeexplore.ieee.org/document/9561022/	[ "Weiming Zhi", "Tin Lai", "Lionel Ott", "Fabio Ramos", "Weiming Zhi", "Tin Lai", "Lionel Ott", "Fabio Ramos" ]	Critical for the coexistence of humans and robots in dynamic environments is the capability for agents to understand each other’s actions, and anticipate their movements. This paper presents Stochastic Process Anticipatory Navigation (SPAN), a framework that enables nonholonomic robots to navigate in environments with crowds, while anticipating and accounting for the motion patterns of pedestrians...
Real-Time Human Lower Limbs Motion Estimation and Feedback for Potential Applications in Robotic Gait Aid and Training	https://ieeexplore.ieee.org/document/9561553/	[ "Lei Wang", "Qingguo Li", "Jingang Yi", "Jinyuan Zhang", "Tao Liu", "Lei Wang", "Qingguo Li", "Jingang Yi", "Jinyuan Zhang", "Tao Liu" ]	Real-time lower limbs motion or gait measurement is an important part in human-robotic interaction for the control of robotic walkers and rehabilitation devices. Laser range finder or infrared sensor that is mounted on the device has been widely used in applications. Although these sensors can provide accurate horizontal motion information of lower limbs during human walking, it is still difficult...
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning	https://ieeexplore.ieee.org/document/9561672/	[ "Jinwook Huh", "Volkan Isler", "Daniel D. Lee", "Jinwook Huh", "Volkan Isler", "Daniel D. Lee" ]	This paper presents c2g-HOF networks which learn to generate cost-to-go functions for manipulator motion planning. The c2g-HOF architecture consists of a cost-to-go function over the configuration space represented as a neural network (c2g-network) as well as a Higher Order Function (HOF) network which outputs the weights of the c2g-network for a given input workspace. Both networks are trained en...
Smooth-RRT*: Asymptotically Optimal Motion Planning for Mobile Robots under Kinodynamic Constraints	https://ieeexplore.ieee.org/document/9560804/	[ "Yiting Kang", "Zhi Yang", "Riya Zeng", "Qi Wu", "Yiting Kang", "Zhi Yang", "Riya Zeng", "Qi Wu" ]	Nowadays, various algorithms based on the Rapidly-exploring Random Tree (RRT) methods are utilized to solve motion planning problems. Based on the RRT*, we developed a novel reconnection method that enables the planner to directly generate a smooth curved trajectory. Meanwhile, kinodynamic constraints of the robots are considered to generate the control input, which improves the feasibility of the...
Continuous Optimization-Based Task and Motion Planning with Signal Temporal Logic Specifications for Sequential Manipulation	https://ieeexplore.ieee.org/document/9561209/	[ "Rin Takano", "Hiroyuki Oyama", "Masaki Yamakita", "Rin Takano", "Hiroyuki Oyama", "Masaki Yamakita" ]	We propose a new optimization-based task and motion planning (TAMP) with signal temporal logic (STL) specifications for robotic sequential manipulation such as pick-and-place tasks. Given a high-level task specification, the TAMP problem is to plan a trajectory that satisfies the specification. This is, however, a challenging problem due to the difficulty of combining continuous motion planning an...
Proximal Policy Optimization with Relative Pearson Divergence	https://ieeexplore.ieee.org/document/9560856/	[ "Taisuke Kobayashi", "Taisuke Kobayashi" ]	The recent remarkable progress of deep reinforcement learning (DRL) stands on regularization of policy for stable and efficient learning. A popular method, named proximal policy optimization (PPO), has been introduced for this purpose. PPO clips density ratio of the latest and baseline policies with a threshold, while its minimization target is unclear. As another problem of PPO, the symmetric thr...
Optimal Object Placement for Minimum Discontinuity Non-revisiting Coverage Task	https://ieeexplore.ieee.org/document/9560853/	[ "Tong Yang", "Jaime Valls Miro", "Yue Wang", "Rong Xiong", "Tong Yang", "Jaime Valls Miro", "Yue Wang", "Rong Xiong" ]	This work considers the optimal non-revisiting coverage tasks with a single non-redundant manipulator for the case when the object can be positioned at a predefined set of locations within the workcell. The scenario is often encountered in typical industrial settings, for instance when the object presents itself along a conveyor belt and its surface can not be serviced at a single location - the o...
Search-Based Online Trajectory Planning for Car-like Robots in Highly Dynamic Environments	https://ieeexplore.ieee.org/document/9560852/	[ "Jiahui Lin", "Tong Zhou", "Delong Zhu", "Jianbang Liu", "Max Q.-H. Meng", "Jiahui Lin", "Tong Zhou", "Delong Zhu", "Jianbang Liu", "Max Q.-H. Meng" ]	This paper presents a search-based partial motion planner for generating feasible trajectories of car-like robots in highly dynamic environments. The planner searches for smooth, safe, and near-time-optimal trajectories by exploring a state graph built on motion primitives. To enable fast online planning, we propose an efficient path searching algorithm based on the aggregation and pruning of moti...
Task-Space Decomposed Motion Planning Framework for Multi-Robot Loco-Manipulation	https://ieeexplore.ieee.org/document/9560902/	[ "Xiaoyu Zhang", "Lei Yan", "Tin Lun Lam", "Sethu Vijayakumar", "Xiaoyu Zhang", "Lei Yan", "Tin Lun Lam", "Sethu Vijayakumar" ]	This paper introduces a novel task-space decomposed motion planning framework for multi-robot simultaneous locomotion and manipulation. When several manipulators hold an object, closed-chain kinematic constraints are formed, and it will make the motion planning problems challenging by inducing lower-dimensional singularities. Unfortunately, the constrained manifold will be even more complicated wh...
SMT-Based Optimal Deployment of Mobile Rechargers	https://ieeexplore.ieee.org/document/9561061/	[ "Tanmoy Kundu", "Indranil Saha", "Tanmoy Kundu", "Indranil Saha" ]	Efficient recharging is an essential requirement for autonomous mobile robots. In an indoor robotic application, charging stations can be installed offline. However, frequent trips to the charging stations cause inefficiency in the performance of the mobile robots. In an outdoor environment, a charging station cannot even be installed easily. We propose a framework and algorithms for enabling a gr...
Fast Replanning Multi-Heuristic A	https://ieeexplore.ieee.org/document/9561928/	[ "Junhyoung Ha", "Soonkyum Kim", "Junhyoung Ha", "Soonkyum Kim" ]	In this paper, we proposed a novel path replanning algorithm on arbitrary graphs. To avoid computationally heavy preprocessing and to reduce required memory to store the expanded vertices of the previous search, we defined the feature vertices, which are extracted from the previous path by a simple algorithm to compare the costs between adjacent vertices along the path once. Proper additional heur...
Generating Large-Scale Trajectories Efficiently using Double Descriptions of Polynomials	https://ieeexplore.ieee.org/document/9561585/	[ "Zhepei Wang", "Hongkai Ye", "Chao Xu", "Fei Gao", "Zhepei Wang", "Hongkai Ye", "Chao Xu", "Fei Gao" ]	For quadrotor trajectory planning, describing a polynomial trajectory through coefficients and end-derivatives both enjoy their own convenience in energy minimization. We name them double descriptions of polynomial trajectories. The transformation between them, causing most of the inefficiency and instability, is formally analyzed in this paper. Leveraging its analytic structure, we design a linea...
Restoring Force Design of Active Self-healing Tension Transmission System and Application to Tendon-driven Legged Robot	https://ieeexplore.ieee.org/document/9561531/	[ "Shinsuke Nakashima", "Kento Kawaharazuka", "Manabu Nishiura", "Yuki Asano", "Yohei Kakiuchi", "Kei Okada", "Koji Kawasaki", "Masayuki Inaba", "Shinsuke Nakashima", "Kento Kawaharazuka", "Manabu Nishiura", "Yuki Asano", "Yohei Kakiuchi", "Kei Okada", "Koji Kawasaki", "Masayuki Inaba" ]	Self-healing function is a promising approach for damage management of high-load robot applications such as legged robots. Although the function is getting major in soft robotics, its application to life-sized "stiff" robots is of relatively minor interest. Although the authors have devised several self-healing tensile modules for tendon-driven robots, the design guideline to satisfy the large loa...
A Translational Parallel Continuum Robot Reinforced by Origami and Cross-Routing Tendons	https://ieeexplore.ieee.org/document/9561429/	[ "Charles Troeung", "Chao Chen", "Charles Troeung", "Chao Chen" ]	We introduce an origami-reinforced parallel continuum robot which is capable of maintaining the orientation of the end effector regardless of the bending shape. The cross-routing tendons provide an effective actuation of the robot because the constant length of the backbones prevent the actuation of parallel arrangement of tendons. We utilise the arclength relationship of parallel curves to show t...
Design of a 3-DOF Coupled Tendon-Driven Waist Joint	https://ieeexplore.ieee.org/document/9561270/	[ "Yiwei Wang", "Wenyang Li", "Shunta Togo", "Hiroshi Yokoi", "Yinlai Jiang", "Yiwei Wang", "Wenyang Li", "Shunta Togo", "Hiroshi Yokoi", "Yinlai Jiang" ]	This paper proposes a coupled tendon-driven waist joint for humanoid robots. The waist joint was designed as a 3 degrees of freedom (DOF) structure to simulate the motion of a human waist. The power transmission was designed by adopting a 3-motor 3-DOF (3M3D) coupled tendon-driven mechanism, so that the torque on the joints was multiplied. We derived the torque transmission formula and the rotatio...
Design and Modeling of a Variable-Stiffness Spring Mechanism for Impedance Modulation in Physical Human–Robot Interaction	https://ieeexplore.ieee.org/document/9560966/	[ "Ronnapee Chaichaowarat", "Satoshi Nishimura", "Hermano Igo Krebs", "Ronnapee Chaichaowarat", "Satoshi Nishimura", "Hermano Igo Krebs" ]	Our goal is to investigate different approaches to modulate stiffness and apply them to human-robot interaction. Here we report on our effort employing the concept of adjustable unsupported-length cantilever leaf spring, which has been previously applied to different designs of variable stiffness actuators. By transmitting the interaction force through the elastic component directly to the support...
Mecanum Crank: A Novel Omni-Directional Vehicle Using Crank Leg	https://ieeexplore.ieee.org/document/9560834/	[ "Satsuya Noda", "Haruki Kunii", "Mutsuki Yaginuma", "Kazushi Yamanobe", "Satsuya Noda", "Haruki Kunii", "Mutsuki Yaginuma", "Kazushi Yamanobe" ]	A vehicle is expected to exhibit omni-directional locomotion capability to provide improved rough terrain vehicle functionality. Generally, rough terrain vehicles are not holonomic and cannot travel in the lateral direction, whereas typical omni-directional vehicles have difficulty in traveling on rough terrain. This paper proposes installing a crank leg for a Mecanum-wheeled vehicle ("Mecanum cra...
Position and Orientation Control of Polygonal Objects by Sensorless In-hand Caging Manipulation	https://ieeexplore.ieee.org/document/9561713/	[ "Shun Komiyama", "Yusuke Maeda", "Shun Komiyama", "Yusuke Maeda" ]	In this work, we propose an approach to manipulate objects by position-controlled robot hands: in-hand caging manipulation. In this method, an object is manipulated based on caging without force sensing or force control. An object is caged by a robot hand throughout manipulation, and we can locate the object around a goal by deformation of the cage without sensing the object configuration. In this...
3D biped locomotion control including seamless transition between walking and running via 3D ZMP manipulation	https://ieeexplore.ieee.org/document/9561503/	[ "Tomomichi Sugihara", "Kenta Imanishi", "Takanobu Yamamoto", "Stéphane Caron", "Tomomichi Sugihara", "Kenta Imanishi", "Takanobu Yamamoto", "Stéphane Caron" ]	A novel control scheme for biped robots to manipulate the ZMP three-dimensionally apart from the actual ground profile is presented. It is shown that the linear inverted-pendulum-like dynamics with this scheme can represent a wider class of movements including variation of the body height. Moreover, this can also represent the motion in aerial phase. Based on this, the foot-guided controller propo...
GCC-PHAT with Speech-oriented Attention for Robotic Sound Source Localization	https://ieeexplore.ieee.org/document/9561885/	[ "Jiadong Wang", "Xinyuan Qian", "Zihan Pan", "Malu Zhang", "Haizhou Li", "Jiadong Wang", "Xinyuan Qian", "Zihan Pan", "Malu Zhang", "Haizhou Li" ]	Robotic audition is a basic sense that helps robots perceive the surroundings and interact with humans. Sound Source Localization (SSL) is an essential module for a robotic system. However, the performance of most sound source localization techniques degrades in noisy and reverberant environments due to inaccurate Time Difference of Arrival (TDoA) estimation. In robotic sound source localization, ...
Towards Robust GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization	https://ieeexplore.ieee.org/document/9562037/	[ "Weisong Wen", "Li-Ta Hsu", "Weisong Wen", "Li-Ta Hsu" ]	Global navigation satellite systems (GNSS) are one of the utterly popular sources for providing globally referenced positioning for autonomous systems. However, the performance of the GNSS positioning is significantly challenged in urban canyons, due to the signal reflection and blockage from buildings. Given the fact that the GNSS measurements are highly environmentally dependent and time-correla...
Camera Relocalization using Deep Point Cloud Generation and Hand-crafted Feature Refinement	https://ieeexplore.ieee.org/document/9561289/	[ "Wang Junyi", "Qi Yue", "Wang Junyi", "Qi Yue" ]	Visual localization plays an indispensable role in robotics. Both learning and hand-crafted feature based methods for relocalization process keep their effectiveness and weakness. However, current algorithms seldom consider these two kinds of features under one framework. In this paper, focusing on this task, we propose a novel relocalization framework for RGB or RGB-D data source, which is compos...
Accelerating Probabilistic Volumetric Mapping using Ray-Tracing Graphics Hardware	https://ieeexplore.ieee.org/document/9561068/	[ "Heajung Min", "Kyung Min Han", "Young J. Kim", "Heajung Min", "Kyung Min Han", "Young J. Kim" ]	Probabilistic volumetric mapping (PVM) represents a 3D environmental map for an autonomous robotic navigational task. A popular implementation such as Octomap is widely used in the robotics community for such a purpose. The Octomap relies on an octree to represent a PVM and its main bottleneck lies in massive ray-shooting to determine the occupancy of the underlying volumetric voxel grids.In this ...
UVIP: Robust UWB aided Visual-Inertial Positioning System for Complex Indoor Environments	https://ieeexplore.ieee.org/document/9561208/	[ "Bo Yang", "Jun Li", "Hong Zhang", "Bo Yang", "Jun Li", "Hong Zhang" ]	Indoor positioning without GPS is a challenge task, especially, in complex scenes or when sensors fail. In this paper, we develop an ultra-wideband aided visual-inertial positioning system (UVIP) which aims to achieve accurate and robust positioning results in complex indoor environments. To this end, a point-line-based stereo visual-inertial odometry (PL-sVIO) is firstly designed to improve the p...
LiDAR-Based Initial Global Localization Using Two-Dimensional (2D) Submap Projection Image (SPI)	https://ieeexplore.ieee.org/document/9560740/	[ "Yanhao Li", "Hao Li", "Yanhao Li", "Hao Li" ]	Initial global localization is important to mobile robotics in terms of navigation initialization (or re-initialization) and loop closure in SLAM. 3D LiDARs are commonly used for mobile robotics, yet LiDAR-based initial global localization (especially at large scale such as in outdoor environments) is still challenging due to lack of salient features in LiDAR range data. Inspired by visual SLAM or...
Automatic Hyper-Parameter Tuning for Black-box LiDAR Odometry	https://ieeexplore.ieee.org/document/9561789/	[ "Kenji Koide", "Masashi Yokozuka", "Shuji Oishi", "Atsuhiko Banno", "Kenji Koide", "Masashi Yokozuka", "Shuji Oishi", "Atsuhiko Banno" ]	LiDAR odometry algorithms are complex and involve a number of hyper-parameters. The choice of hyper-parameters can substantively affect the performance of odometry estimation, and it is necessary to carefully fine-tune the hyper-parameters depending on the sensor, environment, and algorithm to achieve the best estimation results. While odometry estimation algorithms are often tuned manually, this ...
Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling	https://ieeexplore.ieee.org/document/9560915/	[ "Kavisha Vidanapathirana", "Peyman Moghadam", "Ben Harwood", "Muming Zhao", "Sridha Sridharan", "Clinton Fookes", "Kavisha Vidanapathirana", "Peyman Moghadam", "Ben Harwood", "Muming Zhao", "Sridha Sridharan", "Clinton Fookes" ]	Place Recognition enables the estimation of a globally consistent map and trajectory by providing non-local constraints in Simultaneous Localisation and Mapping (SLAM). This paper presents Locus, a novel place recognition method using 3D LiDAR point clouds in large-scale environments. We propose a method for extracting and encoding topological and temporal information related to components in a sc...
Automated Extrinsic Calibration for 3D LiDARs with Range Offset Correction using an Arbitrary Planar Board	https://ieeexplore.ieee.org/document/9561175/	[ "Junha Kim", "Changhyeon Kim", "Youngsoo Han", "H. Jin Kim", "Junha Kim", "Changhyeon Kim", "Youngsoo Han", "H. Jin Kim" ]	This paper proposes an automatic and accuracy- enhanced extrinsic calibration method for 3D LiDARs with a range offset correction, which needs only an arbitrarily-shaped single planar board. One of the most exhaustive parts of existing LiDAR calibration procedures is to manually find target objects from massive point clouds. To obviate user interventions, we propose an automated planar board detec...
Machine Learning-based Human-Following System: Following the Predicted Position of a Walking Human	https://ieeexplore.ieee.org/document/9561691/	[ "Ansheng Wang", "Yasutoshi Makino", "Hiroyuki Shinoda", "Ansheng Wang", "Yasutoshi Makino", "Hiroyuki Shinoda" ]	Human–robot interaction (HRI) has been widely researched in diverse applications. A robot following a person is one such scenario investigated in the HRI field. However, human movements and actions are complex and can change dramatically. We herein demonstrate a machine learning-based system that allows a person-following robot to track in real-time the predicted future motion of a walking human, ...
Anytime Game-Theoretic Planning with Active Reasoning About Humans’ Latent States for Human-Centered Robots	https://ieeexplore.ieee.org/document/9561463/	[ "Ran Tian", "Liting Sun", "Masayoshi Tomizuka", "David Isele", "Ran Tian", "Liting Sun", "Masayoshi Tomizuka", "David Isele" ]	A human-centered robot needs to reason about the cognitive limitation and potential irrationality of its human partner to achieve seamless interactions. This paper proposes an anytime game-theoretic planner that integrates iterative reasoning models, a partially observable Markov decision process, and chance-constrained Monte-Carlo belief tree search for robot behavioral planning. Our planner enab...
Momentum Observer-Based Collision Detection Using LSTM for Model Uncertainty Learning	https://ieeexplore.ieee.org/document/9561667/	[ "Daegyu Lim", "Donghyeon Kim", "Jaeheung Park", "Daegyu Lim", "Donghyeon Kim", "Jaeheung Park" ]	As robots begin to collaborate with people in real life, safety needs to be rigorously ensured to reliably employ robots nearby. In addition to collision prevention algorithms, studies are being actively conducted on collision handling methods. Momentum Observer (MOB) was developed to estimate disturbance torque without using joint acceleration. However, the estimated disturbance from MOB contains...
Deep Learning and Mixed Reality to Autocomplete Teleoperation	https://ieeexplore.ieee.org/document/9560887/	[ "Mohammad Kassem Zein", "Majd Al Aawar", "Daniel Asmar", "Imad H. Elhajj", "Mohammad Kassem Zein", "Majd Al Aawar", "Daniel Asmar", "Imad H. Elhajj" ]	Teleoperation of robots can be challenging, especially for novice users with little to no experience at such tasks. The difficulty is largely due to the numerous degrees of freedom users must control and their limited perception bandwidth. To help mitigate these challenges, we propose in this paper a solution which relies on artificial intelligence to understand user intended motion and then on mi...
Learning Spatial Context with Graph Neural Network for Multi-Person Pose Grouping	https://ieeexplore.ieee.org/document/9561960/	[ "J Jiahao Lin", "Gim Hee Lee", "J Jiahao Lin", "Gim Hee Lee" ]	Bottom-up approaches for image-based multi-person pose estimation consist of two stages: (1) keypoint detection and (2) grouping of the detected keypoints to form person instances. Current grouping approaches rely on learned embedding from only visual features that completely ignore the spatial configuration of human poses. In this work, we formulate the grouping task as a graph partitioning probl...
Automatic Hanging Point Learning from Random Shape Generation and Physical Function Validation	https://ieeexplore.ieee.org/document/9561484/	[ "Kosuke Takeuchi", "Iori Yanokura", "Yohei Kakiuchi", "Kei Okada", "Masayuki Inaba", "Kosuke Takeuchi", "Iori Yanokura", "Yohei Kakiuchi", "Kei Okada", "Masayuki Inaba" ]	The purpose of this paper is the robotic hanging manipulation of an object of various shapes that is not limited to a specific category. To achieve this, we propose a method that allows the estimator to learn many different shapes with hanging points without any manual annotation. A random shape generator using GAN solves the limitation of the number of 3D models and can handle objects of various ...
Graph Convolutional Network based Configuration Detection for Freeform Modular Robot Using Magnetic Sensor Array	https://ieeexplore.ieee.org/document/9561340/	[ "Yuxiao Tu", "Guanqi Liang", "Tin Lun Lam", "Yuxiao Tu", "Guanqi Liang", "Tin Lun Lam" ]	Modular self-reconfigurable robotic (MSRR) systems are potentially more robust and more adaptive than conventional systems. Following our previous work where we proposed a freeform MSRR module called FreeBOT, this paper presents a novel configuration detection system for FreeBOT using a magnetic sensor array. A FreeBOT module can be connected by up to 11 modules, and the proposed configuration det...
An analytical diabolo model for robotic learning and control	https://ieeexplore.ieee.org/document/9561578/	[ "Felix von Drigalski", "Devwrat Joshi", "Takayuki Murooka", "Kazutoshi Tanaka", "Masashi Hamaya", "Yoshihisa Ijiri", "Felix von Drigalski", "Devwrat Joshi", "Takayuki Murooka", "Kazutoshi Tanaka", "Masashi Hamaya", "Yoshihisa Ijiri" ]	In this paper, we present a diabolo model that can be used for training agents in simulation to play diabolo, as well as running it on a real dual robot arm system. We first derive an analytical model of the diabolo-string system and compare its accuracy using data recorded via motion capture, which we release as a public dataset of skilled play with diabolos of different dynamics. We show that ou...

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ICRA 2021 Accepted Paper Meta Info Dataset

This dataset is collect from the ICRA 2021 IEEE International Conference on Robotics and Automation (ICRA) 2021 accepted papers' meta info (https://ieeexplore.ieee.org/xpl/conhome/9560720/proceeding) as well as the arxiv website DeepNLP paper arxiv (http://www.deepnlp.org/content/paper/icra2021). For researchers who are interested in doing analysis of ICRA 2021 accepted papers and potential trends, you can use the already cleaned up json files. Each row contains the meta information of a paper in the ICRA 2021 conference. To explore more AI & Robotic papers (NIPS/ICML/ICLR/IROS/ICRA/etc) and AI equations, feel free to navigate the Equation Search Engine (http://www.deepnlp.org/search/equation) as well as the AI Agent Search Engine to find the deployed AI Apps and Agents (http://www.deepnlp.org/search/agent) in your domain.

Equations Latex code and Papers Search Engine

Meta Information of Json File of Paper

{
    "title": "Online Prediction of Lane Change with a Hierarchical Learning-Based Approach",
    "detail_url": "https://ieeexplore.ieee.org/document/9812269/",
    "author_list": ["Xishun Liao", "Ziran Wang", "Xuanpeng Zhao", "Zhouqiao Zhao", "Kyungtae Han", "Prashant Tiwari", "Matthew J. Barth", "Guoyuan Wu", "Xishun Liao", "Ziran Wang", "Xuanpeng Zhao", "Zhouqiao Zhao", "Kyungtae Han", "Prashant Tiwari", "Matthew J. Barth", "Guoyuan Wu"],
    "abstract": "In the foreseeable future, connected and auto-mated vehicles (CAVs) and human-driven vehicles will share the road networks together. In such a mixed traffic environment, CAVs need to understand and predict maneuvers of surrounding vehicles for safer and more efficient interactions, especially when human drivers bring in a wide range of uncertainties. In this paper, we propose a learning-based lane..."
}