Trajectory optimization with hybrid probabilistic roadmap approach to achieve time efficient navigation of unmanned vehicles in unstructured environment
Robotic Intelligence and Automation
ISSN: 2754-6969
Article publication date: 9 February 2024
Issue publication date: 29 March 2024
Abstract
Purpose
This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.
Design/methodology/approach
Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.
Findings
The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.
Originality/value
The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.
Keywords
Acknowledgements
Acknowledgement: No funds/grant is received.
Data availability: Data will be provided on request.
Citation
Singh, R. (2024), "Trajectory optimization with hybrid probabilistic roadmap approach to achieve time efficient navigation of unmanned vehicles in unstructured environment", Robotic Intelligence and Automation, Vol. 44 No. 1, pp. 164-189. https://doi.org/10.1108/RIA-08-2023-0107
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited