activity
20162022
most citedRigid-Soft Interactive Learning for Robust Grasping

24 citations · 51 across the 12 of their papers we have counts for

collaborators

28 papers

cs.RO20221 cited

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…

cs.RO20211 cited

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…

cs.RO2021

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…

cs.RO20201 cited

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…

cs.RO20202 cited

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…

cs.RO20203 cited

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.…