Paper
3 April 2023 Application research of landmarks in path planning algorithms of mobile robots
Linghao Fan, Xiangde Liu, Yi Zhang
Author Affiliations +
Proceedings Volume 12599, Second International Conference on Digital Society and Intelligent Systems (DSInS 2022); 1259920 (2023) https://doi.org/10.1117/12.2673373
Event: 2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022), 2022, Chendgu, China
Abstract
A way of incorporating landmark information matrix QR to affect the global path planning algorithm is proposed for the use of landmarks in robot localization and navigation. It is also investigated how this method affects the pace at which the original algorithm solves problems. The reward and punishment items in this technique include dangerous locations with lots of obstacles around them, landmarks with location information connected to the ground, and the two combined. Three representative common robot path planning algorithms are also imposed as influences. Through MATLAB simulation experiment, find the optimal path planning algorithm that is appropriate for applying reward and punishment by comparing the quality of the robot's driving path and the algorithm solution speed before and after the reward and punishment. According to the simulation results, the reward and punishment approach is practical and efficient. The heuristic search algorithm is better suited for reward and punishment, and both its path quality and speed of solution have greatly increased.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Linghao Fan, Xiangde Liu, and Yi Zhang "Application research of landmarks in path planning algorithms of mobile robots", Proc. SPIE 12599, Second International Conference on Digital Society and Intelligent Systems (DSInS 2022), 1259920 (3 April 2023); https://doi.org/10.1117/12.2673373
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KEYWORDS
Genetic algorithms

Evolutionary algorithms

Matrices

Computer simulations

Mobile robots

Mathematical optimization

Algorithm development

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