Path planning for mobile robot using sonar map and neural network

Jin Cao; Wen-chuan Chiang; Terrell Nathan Mundhenk; Ernest L. Hall

doi:10.1117/12.325771

6 October 1998 Path planning for mobile robot using sonar map and neural network

Jin Cao, Wen-chuan Chiang, Terrell Nathan Mundhenk, Ernest L. Hall

Proceedings Volume 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision; (1998) https://doi.org/10.1117/12.325771
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

The purpose of this paper is to present a new approach for path planing of a mobile robot in static outdoor environments. A simple sensor model is developed for fast acquisition of environment information. The obstacle avoidance system is based on a micro-controller interfaced with multiple ultrasonic transducers with a rotating motor. Using sonar readings and environment knowledge, a local map based on weight evaluation function is built for the robot path planing. The path planner finds the local optimal path using the A* search algorithm. The robot is trained to learn a goal-directed task under adequate supervision. The simulation experiments show that a robot, utilizing our neural network scheme, can learn tasks of obstacle avoidance in the work space of a certain geometrical complexity. The result shows that the proposed algorithm can be efficiently implemented in an outdoor environment.

Citation Download Citation

Jin Cao, Wen-chuan Chiang, Terrell Nathan Mundhenk, and Ernest L. Hall "Path planning for mobile robot using sonar map and neural network", Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); https://doi.org/10.1117/12.325771

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