8 papers
PILOT: Privileged Imitation Learning for End-to-End Motion Planning of Autonomous UAVs under Partial Observability
Qingrui Zhang, Feng Xue, Xiang Zhou +1
Autonomous navigation in cluttered environments is hampered by partial observability and dynamic constraints. This paper presents PILOT, a constraint-aware privileged imitation lea…
HAC-LOCO: Learning Hierarchical Active Compliance Control for Quadruped Locomotion under Continuous External Disturbances
Xiang Zhou, Xinyu Zhang, Qingrui Zhang
Despite recent remarkable achievements in quadruped control, it remains challenging to ensure robust and compliant locomotion in the presence of unforeseen external disturbances. E…
PA-LOCO: Learning Perturbation-Adaptive Locomotion for Quadruped Robots
Zhiyuan Xiao, Xinyu Zhang, Xiang Zhou +1
Numerous locomotion controllers have been designed based on Reinforcement Learning (RL) to facilitate blind quadrupedal locomotion traversing challenging terrains. Nevertheless, lo…
GRF-based Predictive Flocking Control with Dynamic Pattern Formation
Chenghao Yu, Dengyu Zhang, Qingrui Zhang
It is promising but challenging to design flocking control for a robot swarm to autonomously follow changing patterns or shapes in a optimal distributed manner. The optimal flockin…
SYNLOCO: Synthesizing Central Pattern Generator and Reinforcement Learning for Quadruped Locomotion
Xinyu Zhang, Zhiyuan Xiao, Qingrui Zhang +1
The Central Pattern Generator (CPG) is adept at generating rhythmic gait patterns characterized by consistent timing and adequate foot clearance. Yet, its open-loop configuration o…
Reinforced Potential Field for Multi-Robot Motion Planning in Cluttered Environments
Dengyu Zhang, Xinyu Zhang, Zheng Zhang +2
Motion planning is challenging for multiple robots in cluttered environments without communication, especially in view of real-time efficiency, motion safety, distributed computati…
Multi-Robot Motion Planning: A Learning-Based Artificial Potential Field Solution
Dengyu Zhang, Guobin Zhu, Qingrui Zhang
Motion planning is a crucial aspect of robot autonomy as it involves identifying a feasible motion path to a destination while taking into consideration various constraints, such a…
Distributed Flocking Control of Aerial Vehicles Based on a Markov Random Field
Guobin Zhu, Shanwei Fan, Qingrui Zhang
The distributed flocking control of collective aerial vehicles has extraordinary advantages in scalability and reliability, \emph{etc.} However, it is still challenging to design a…