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20232026
most citedOnline Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning

19 citations · 19 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2026

AgilePE: Autonomous UAV Pursuit-Evasion via Self-Play Reinforcement Learning

Wenhao Tang, Tianyang Chen, Zhejun Cui +9

Autonomous pursuit-evasion is a fundamental challenge for Unmanned Aerial Vehicles (UAVs), requiring rapid decision-making under tightly coupled dynamics and continuously changing…

cs.LG2025

Automatic Reward Shaping from Multi-Objective Human Heuristics

Yuqing Xie, Jiayu Chen, Wenhao Tang +3

Designing effective reward functions remains a central challenge in reinforcement learning, especially in multi-objective environments. In this work, we propose Multi-Objective Rew…

cs.RO2025

JuggleRL: Mastering Ball Juggling with a Quadrotor via Deep Reinforcement Learning

Shilong Ji, Yinuo Chen, Chuqi Wang +9

Aerial robots interacting with objects must perform precise, contact-rich maneuvers under uncertainty. In this paper, we study the problem of aerial ball juggling using a quadrotor…

cs.RO2025

Hysteresis-Aware Neural Network Modeling and Whole-Body Reinforcement Learning Control of Soft Robots

Zongyuan Chen, Yan Xia, Jiayuan Liu +10

Soft robots exhibit inherent compliance and safety, which makes them particularly suitable for applications requiring direct physical interaction with humans, such as surgical proc…

cs.RO2024

What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Study

Jiayu Chen, Chao Yu, Yuqing Xie +9

Executing precise and agile flight maneuvers is critical for quadrotors in various applications. Traditional quadrotor control approaches are limited by their reliance on flat traj…

cs.RO2024

Multi-UAV Formation Control with Static and Dynamic Obstacle Avoidance via Reinforcement Learning

Yuqing Xie, Chao Yu, Hongzhi Zang +7

This paper tackles the challenging task of maintaining formation among multiple unmanned aerial vehicles (UAVs) while avoiding both static and dynamic obstacles during directed fli…

cs.RO2024★ 19 cited

Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning

Jiayu Chen, Chao Yu, Guosheng Li +6

Multi-UAV pursuit-evasion, where pursuers aim to capture evaders, poses a key challenge for UAV swarm intelligence. Multi-agent reinforcement learning (MARL) has demonstrated poten…

cs.LG2023

A Dual Curriculum Learning Framework for Multi-UAV Pursuit-Evasion in Diverse Environments

Jiayu Chen, Guosheng Li, Chao Yu +4

This paper addresses multi-UAV pursuit-evasion, where a group of drones cooperates to capture a fast evader in a confined environment with obstacles. Existing heuristic algorithms,…

cs.LG2023

MASP: Scalable GNN-based Planning for Multi-Agent Navigation

Xinyi Yang, Xinting Yang, Chao Yu +4

We investigate multi-agent navigation tasks, where multiple agents need to reach initially unassigned goals in a limited time. Classical planning-based methods suffer from expensiv…

cs.RO2023

Active Neural Topological Mapping for Multi-Agent Exploration

Xinyi Yang, Yuxiang Yang, Chao Yu +5

This paper investigates the multi-agent cooperative exploration problem, which requires multiple agents to explore an unseen environment via sensory signals in a limited time. A po…

cs.LG2023

Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning

Jiayu Chen, Zelai Xu, Yunfei Li +6

Learning Nash equilibrium (NE) in complex zero-sum games with multi-agent reinforcement learning (MARL) can be extremely computationally expensive. Curriculum learning is an effect…