An adaptive coverage path planning method considering energy constraints

Song Shao

doi:10.1117/12.2672136

16 March 2023 An adaptive coverage path planning method considering energy constraints

Song Shao

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 1259310 (2023) https://doi.org/10.1117/12.2672136
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

Coverage path planning algorithms are widely used by many robots conducting work like floor sweeping, map generating and underwater searching. One of the practical methods is the Backtracking Spiral Algorithm (BSA), which is efficient and complete coverage guaranteed. In practice, however, autonomous robots are faced with the problem of energy constraints. The duration of the battery of a robot is usually limited. This paper presents an adaptive coverage path planning method based on BSA considering the energy constraints. The objective of this method is to minimise the total length of the path the robot travelled to recharge while guaranteeing complete coverage. This method uses an estimation strategy which would use the energy consumption of the last round as a conjecture of that of the next round and recharge when the remaining energy would probably be insufficient to complete the next round while the robot passes nearby the recharging station. A simulation result is then provided to serve as proof of this method.

Citation Download Citation

Song Shao "An adaptive coverage path planning method considering energy constraints", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 1259310 (16 March 2023); https://doi.org/10.1117/12.2672136

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