Multi-robot Target Encirclement Control with Collision Avoidance via Deep Reinforcement Learning

Junchong Ma; Huimin Lu; Junhao Xiao; Zhiwen Zeng; Zhiqiang Zheng

doi:10.1007/s10846-019-01106-x

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-robot Target Encirclement Control with Collision Avoidance via Deep Reinforcement Learning

Junchong Ma Huimin Lu Junhao Xiao Zhiwen Zeng Zhiqiang Zheng

Year: 2019 Journal: Journal of Intelligent & Robotic Systems Vol: 99 (2)Pages: 371-386 Publisher: Springer Science+Business Media

DOI: 10.1007/s10846-019-01106-x

Get Full-Text PDF Get Analytical Report

Keywords:

Reinforcement learning Patrolling Robot Collision avoidance Computer science Artificial intelligence Control (management) Engineering Collision Computer security Law

Metrics

Cited By

3.88

FWCI (Field Weighted Citation Impact)

Refs

0.94

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Distributed Control Multi-Agent Systems

Physical Sciences → Computer Science → Computer Networks and Communications

Underwater Vehicles and Communication Systems

Physical Sciences → Engineering → Ocean Engineering

Reinforcement Learning in Robotics

Physical Sciences → Computer Science → Artificial Intelligence

Multi-robot Target Encirclement Control with Collision Avoidance via Deep Reinforcement Learning

Metrics

Citation History

Topics

Related Documents

Multi-Target Encirclement with Collision Avoidance via Deep Reinforcement Learning using Relational Graphs

Multi-Robot Collision Avoidance with Map-based Deep Reinforcement Learning

Decentralized multi-robot encirclement of a 3D target with guaranteed collision avoidance

Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning

Formation Control with Collision Avoidance through Deep Reinforcement Learning