Rapidly-exploring Random Trees multi-robot map exploration under optimization framework-Reference-Cited by-同舟云学术

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Rapidly-exploring Random Trees multi-robot map exploration under optimization framework

Published:2020-09 Issue: Volume:131 Page:103565
ISSN:0921-8890
Container-title:Robotics and Autonomous Systems
language:en
Short-container-title:Robotics and Autonomous Systems

Author:

Zhang Liwei,Lin Zhibin,Wang Jie,He Bingwei

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province, China

Program for New Century Excellent Talents in Fujian Province University, China

German Science Foundation (DFG), Germany

National Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference35 articles.

1. C. Craye, D. Filliat, J.-F. Goudou, RL-IAC: An exploration policy for online saliency learning on an autonomous mobile robot, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016, pp. 4877–4884.

2. R. Ramaithititima, S. Bhattacharya, Landmark-based exploration with swarm of resource constrained robots, in: IEEE International Conference on Robotics & Automation, 2018, pp. 5034–5041.

3. A.W. Palmer, A.J. Hill, S.J. Scheding, Modelling resource contention in multi-robot task allocation problems with uncertain timing, in: IEEE International Conference on Robotics & Automation, 2018, pp. 3693–3700.

4. M.G. Jadidi, J.V. Miro, G. Dissanayake, Mutual information-based exploration on continuous occupancy maps, in: IEEE/RSJ International Conference on Intelligent Robots & Systems, 2015, pp. 6086–6092.

5. S. Bai, F. Chen, B. Englot, Toward autonomous mapping and exploration for mobile robots through deep supervised learning, in: IEEE International Conference on Robotics & Automation, 2017, pp. 2379–2384.

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