Coverage Path Planning Using Reinforcement Learning-Based TSP for hTetran—A Polyabolo-Inspired Self-Reconfigurable Tiling Robot

Coverage Path Planning Using Reinforcement Learning-Based TSP for hTetran—A Polyabolo-Inspired Self-Reconfigurable Tiling Robot

One of the critical challenges in deploying the cleaning robots is the completion of covering the entire area. Current tiling robots for area coverage have fixed forms and are limited to cleaning only certain areas. The reconfigurable system is the creative answer to such an optimal coverage problem...

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Bibliographic Details
Main Authors: Anh Vu Le, Prabakaran Veerajagadheswar, Phone Thiha Kyaw, Mohan Rajesh Elara, Nguyen Huu Khanh Nhan
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Sensors
Subjects:
reconfigurable system
tiling robotic
reinforcement learning TSP, complete path planning
energy-aware reward function
Online Access:https://www.mdpi.com/1424-8220/21/8/2577

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https://www.mdpi.com/1424-8220/21/8/2577

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