69 citations · 335 across the 44 of their papers we have counts for
44 papers
TacGNN:Learning Tactile-based In-hand Manipulation with a Blind Robot
Linhan Yang, Bidan Huang, Qingbiao Li +4
In this paper, we propose a novel framework for tactile-based dexterous manipulation learning with a blind anthropomorphic robotic hand, i.e. without visual sensing. First, object-…
RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments
Ruihua Han, Shuai Wang, Shuaijun Wang +5
Autonomous motion planning is challenging in multi-obstacle environments due to nonconvex collision avoidance constraints. Directly applying numerical solvers to these nonconvex fo…
A Generalized Continuous Collision Detection Framework of Polynomial Trajectory for Mobile Robots in Cluttered Environments
Zeqing Zhang, Yinqiang Zhang, Ruihua Han +2
In this paper, we introduce a generalized continuous collision detection (CCD) framework for the mobile robot along the polynomial trajectory in cluttered environments including va…
Learn to Predict How Humans Manipulate Large-sized Objects from Interactive Motions
Weilin Wan, Lei Yang, Lingjie Liu +7
Understanding human intentions during interactions has been a long-lasting theme, that has applications in human-robot interaction, virtual reality and surveillance. In this study,…
Reinforcement Learned Distributed Multi-Robot Navigation with Reciprocal Velocity Obstacle Shaped Rewards
Ruihua Han, Shengduo Chen, Shuaijun Wang +4
The challenges to solving the collision avoidance problem lie in adaptively choosing optimal robot velocities in complex scenarios full of interactive obstacles. In this paper, we…
An Intelligent Self-driving Truck System For Highway Transportation
Dawei Wang, Lingping Gao, Ziquan Lan +9
Recently, there have been many advances in autonomous driving society, attracting a lot of attention from academia and industry. However, existing works mainly focus on cars, extra…
DiffSRL: Learning Dynamical State Representation for Deformable Object Manipulation with Differentiable Simulator
Sirui Chen, Yunhao Liu, Jialong Li +3
Dynamic state representation learning is an important task in robot learning. Latent space that can capture dynamics related information has wide application in areas such as accel…
Learning Selective Communication for Multi-Agent Path Finding
Ziyuan Ma, Yudong Luo, Jia Pan
Learning communication via deep reinforcement learning (RL) or imitation learning (IL) has recently been shown to be an effective way to solve Multi-Agent Path Finding (MAPF). Howe…
Challenges and Outlook in Robotic Manipulation of Deformable Objects
Jihong Zhu, Andrea Cherubini, Claire Dune +10
Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new a…
Learning-based Optoelectronically Innervated Tactile Finger for Rigid-Soft Interactive Grasping
Linhan Yang, Xudong Han, Weijie Guo +3
This paper presents a novel design of a soft tactile finger with omni-directional adaptation using multi-channel optical fibers for rigid-soft interactive grasping. Machine learnin…
Crowd-Driven Mapping, Localization and Planning
Tingxiang Fan, Dawei Wang, Wenxi Liu +1
Navigation in dense crowds is a well-known open problem in robotics with many challenges in mapping, localization, and planning. Traditional solutions consider dense pedestrians as…
Design of an Optoelectronically Innervated Gripper for Rigid-Soft Interactive Grasping
Linhan Yang, Xudong Han, Weijie Guo +4
Over the past few decades, efforts have been made towards robust robotic grasping, and therefore dexterous manipulation. The soft gripper has shown their potential in robust graspi…
Optimization-Based Framework for Excavation Trajectory Generation
Yajue Yang, Pinxin Long, Jia Pan +2
In this paper, we present a novel optimization-based framework for autonomous excavator trajectory generation under various objectives, including minimum joint displacement and min…
Autonomous Social Distancing in Urban Environments using a Quadruped Robot
Tingxiang Fan, Zhiming Chen, Xuan Zhao +5
COVID-19 pandemic has become a global challenge faced by people all over the world. Social distancing has been proved to be an effective practice to reduce the spread of COVID-19.…
Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator
Yajue Yang, Jia Pan, Pinxin Long +2
In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates th…
Keyfilter-Aware Real-Time UAV Object Tracking
Yiming Li, Changhong Fu, Ziyuan Huang +2
Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter…
Rigid-Soft Interactive Learning for Robust Grasping
Linhan Yang, Fang Wan, Haokun Wang +4
Inspired by widely used soft fingers on grasping, we propose a method of rigid-soft interactive learning, aiming at reducing the time of data collection. In this paper, we classify…
A Configuration-Space Decomposition Scheme for Learning-based Collision Checking
Yiheng Han, Wang Zhao, Jia Pan +3
Motion planning for robots of high degrees-of-freedom (DOFs) is an important problem in robotics with sampling-based methods in configuration space C as one popular solution. Recen…
Reciprocal Collision Avoidance for General Nonlinear Agents using Reinforcement Learning
Hao Li, Bowen Weng, Abhishek Gupta +2
Finding feasible and collision-free paths for multiple nonlinear agents is challenging in the decentralized scenarios due to limited available information of other agents and compl…
Learning Resilient Behaviors for Navigation Under Uncertainty
Tingxiang Fan, Pinxin Long, Wenxi Liu +3
Deep reinforcement learning has great potential to acquire complex, adaptive behaviors for autonomous agents automatically. However, the underlying neural network polices have not…
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance
Qingyang Tan, Tingxiang Fan, Jia Pan +1
We present a novel algorithm (DeepMNavigate) for global multi-agent navigation in dense scenarios using deep reinforcement learning (DRL). Our approach uses local and global inform…
Augmented Memory for Correlation Filters in Real-Time UAV Tracking
Yiming Li, Changhong Fu, Fangqiang Ding +2
The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements. Previous appearances are also gradually forgot…
Intervention Aided Reinforcement Learning for Safe and Practical Policy Optimization in Navigation
Fan Wang, Bo Zhou, Ke Chen +5
Combining deep neural networks with reinforcement learning has shown great potential in the next-generation intelligent control. However, there are challenges in terms of safety an…
Deep Learning Scooping Motion using Bilateral Teleoperations
Hitoe Ochi, Weiwei Wan, Yajue Yang +3
We present bilateral teleoperation system for task learning and robot motion generation. Our system includes a bilateral teleoperation platform and a deep learning software. The de…