73 citations · 75 across the 12 of their papers we have counts for
8 papers · 1 filter
DeepMF: Deep Motion Factorization for Closed-Loop Safety-Critical Driving Scenario Simulation
Yizhe Li, Linrui Zhang, Xueqian Wang +2
Safety-critical traffic scenarios are of great practical relevance to evaluating the robustness of autonomous driving (AD) systems. Given that these long-tail events are extremely…
Novelty-based Sample Reuse for Continuous Robotics Control
Ke Duan, Kai Yang, Houde Liu +1
In reinforcement learning, agents collect state information and rewards through environmental interactions, essential for policy refinement. This process is notably time-consuming,…
Efficient Collision Detection Framework for Enhancing Collision-Free Robot Motion
Xiankun Zhu, Yucheng Xin, Shoujie Li +3
Fast and efficient collision detection is essential for motion generation in robotics. In this paper, we propose an efficient collision detection framework based on the Signed Dist…
MuxHand: A Cable-driven Dexterous Robotic Hand Using Time-division Multiplexing Motors
Jianle Xu, Shoujie Li, Hong Luo +4
The robotic dexterous hand is responsible for both grasping and dexterous manipulation. The number of motors directly influences both the dexterity and the cost of such systems. In…
Range-SLAM: Ultra-Wideband-Based Smoke-Resistant Real-Time Localization and Mapping
Yi Liu, Zhuozhu Jian, Shengtao Zheng +4
This paper presents Range-SLAM, a real-time, lightweight SLAM system designed to address the challenges of localization and mapping in environments with smoke and other harsh condi…
Safe Expeditious Whole-Body Control of Mobile Manipulators for Collision Avoidance
Bingjie Chen, Yancong Wei, Rihao Liu +5
Whole-body reactive obstacle avoidance for mobile manipulators (MM) remains an open research problem. Control Barrier Functions (CBF), combined with Quadratic Programming (QP), hav…
CushionCatch: A Compliant Catching Mechanism for Mobile Manipulators via Combined Optimization and Learning
Bingjie Chen, Keyu Fan, Qi Yang +6
Catching flying objects with a cushioning process is a skill commonly performed by humans, yet it remains a significant challenge for robots. In this paper, we present a framework…
Agile and versatile bipedal robot tracking control through reinforcement learning
Jiayi Li, Linqi Ye, Yi Cheng +2
The remarkable athletic intelligence displayed by humans in complex dynamic movements such as dancing and gymnastics suggests that the balance mechanism in biological beings is dec…