Abstract
In this paper we propose a new application sensor-based navigation method for navigation of wheeled mobile robot, based on neural dynamic programming (NDP). We discuss a sensor-based approach to path design and control of wheeled mobile robot (WMR) in an unknown 2-D environment with static obstacles. A strategy of navigation is developed including two main behaviors: a reaching the middle of a collision-free space behavior, and a goal-seeking. The NDP navigator which is the main theme of this paper, can fuse behaviors so that the mobile robot can go for the goal position without colliding with obstacles for the concave and convex obstacles. This solution is based on the reinforcement learning (RL) method of actor-critic architecture for continuous-time, and does not require pre-learning and working on-line. Computer simulations have been conducted to illustrate the performance of the proposed solution by a series of experiments.
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Hendzel, Z., Kołodziej, M. (2022). Neural Dynamic Programming with Application to Wheeled Mobile Robot. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. AUTOMATION 2022. Advances in Intelligent Systems and Computing, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-031-03502-9_22
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DOI: https://doi.org/10.1007/978-3-031-03502-9_22
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