Robot path planning in narrow environments using improved roadmap sampling

Ravankar, Ankit A., Ravankar, Abhijeet, Tafrishi, Seyed Amir ORCID: https://orcid.org/0000-0001-9829-3144, Salazar Luces, Jose Victorio and Hirata, Yasuhisa 2022. Robot path planning in narrow environments using improved roadmap sampling. Presented at: The Proceedings of JSME Annual Conference on Robotics and Mechatronics (Robomec), Japan, 01-04 June 2022. The Proceedings of JSME Annual Conference on Robotics and Mechatronics (Robomec). , vol.2022 JSME, 2P2-M03. 10.1299/jsmermd.2022.2P2-M03

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Abstract

Path planning is a fundamental problem in mobile robots that optimize the path to determine how the robot reaches its goal. In particular sampling-based methods are popular in robotics. However, the sampling-based method is unsuitable for dynamic and narrow environments, unlike the adaptive method due to its prior planning before moving. Moreover, applying the sampling-based method in real-time and dynamic environments becomes more difficult due to its high computational cost. In this paper, we propose an efficient sampling method for roadmap planners to decrease its computational cost and increase the success rate of path planning. The proposed method applies the artificial potential method and map-decomposition method to roadmap planners such as PRM to achieve the goal.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	JSME
ISSN:	2424-3124
Last Modified:	25 Jan 2023 13:48
URI:	https://orca.cardiff.ac.uk/id/eprint/156228

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