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20222026
most citedOnline Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning

19 citations · 70 across the 28 of their papers we have counts for

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6 papers · 1 filter

cs.RO2026

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks

Yujin Wang, Junli Chen, Yixuan Li +4

Embodied foundation models have recently been widely used to improve robot generalization and task success rates. Previous works apply lossy efficient-inference techniques such as…

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★ 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.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.RO2023★ 3 cited

Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation

Xinyi Yang, Shiyu Huang, Yiwen Sun +5

This paper investigates the multi-agent navigation problem, which requires multiple agents to reach the target goals in a limited time. Multi-agent reinforcement learning (MARL) ha…

cs.RO2023★ 11 cited

Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Exploration

Chao Yu, Xinyi Yang, Jiaxuan Gao +8

We consider the problem of cooperative exploration where multiple robots need to cooperatively explore an unknown region as fast as possible. Multi-agent reinforcement learning (MA…