Hierarchical path planner for unknown space exploration using reinforcement learning-based intelligent frontier selection-Reference-Cited by-同舟云学术

Hierarchical path planner for unknown space exploration using reinforcement learning-based intelligent frontier selection

Published:2023-11 Issue: Volume:230 Page:120630
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Fan Jie,Zhang Xudong^ORCID,Zou Yuan

Funder

Natural Science Foundation of Beijing Municipality

China Academy of Space Technology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference45 articles.

1. Adaptive control and intersections with reinforcement learning;Annaswamy;Annual Review of Control, Robotics, and Autonomous Systems,2023

2. Birkin (2016, August 2). Rise of the Robots in the Cleaning Industry. European Cleaning Journal. https://www.birkingroup.co.uk/news/rise-robots-cleaning-industry.

3. Safe learning in robotics: from learning-based control to safe reinforcement learning;Brunke;Annual Review of Control, Robotics, and Autonomous Systems,2022

4. Modular deep reinforcement learning for continuous motion planning with temporal logic;Cai;IEEE Robotics and Automation Letters,2021

5. Robotic space exploration agents;Chien;Science Robotics,2017

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