Kai Zhao
North China University of Water Resources and Electric Power, Henan, 450045, Zhengzhou, China
ABSTRACT
This study presents an environment perception method using for mobile Robots based on ultrasonic probability grid map feature points extraction and matching. Low-cost ultrasonic sensors as the design scheme of distance measuring is adopted. Aiming to obtain the probability of grid map update effectively, an improved Bayesian formula is proposed. To realize synchronous positioning and map construction, dynamic random objects are related to the map with edge detection algorithm. Then the motion of the next step of robot is planned by improved particle swarm algorithm. The result of the numerical simulation shows that the novel particle swarm optimization is effective and can find the more optimal global solutions with high efficiency compared to the basic PSO. The simulation result shows that the method prpposed in this study is feasible and effective and the result obtained is effictivly to the application of robot in complex environment and realize real-time dynamic collision avoidance path planning.
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How to cite this article
Kai Zhao, 2013. Path Planning in Unknown Environment for Mobile Robots Based on Improved Bayes and PSO. Information Technology Journal, 12: 8147-8152.
DOI: 10.3923/itj.2013.8147.8152
URL: https://scialert.net/abstract/?doi=itj.2013.8147.8152
DOI: 10.3923/itj.2013.8147.8152
URL: https://scialert.net/abstract/?doi=itj.2013.8147.8152
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