A Sliding-Mode Control Algorithm of Self-Learning and Obstacle Avoidance for Mobile Robots
Tian Tian, Qiuyue Jiang, Zhengying Cai · The Internet of Things · 2017
It is generally very difficult to make effective obstacle avoidance for mobile robots, especially in uncertain environments. This article models the obstacle avoidance problem as a nonlinear sliding mode, using the self-learning method of non-linear system. First, a sliding mode algorithm is proposed for state dependent layers of the mobile robots, in which two kinds of boundary layers are included in, namely a sector-shaped layer and a constant layer. Second, a multi-input algorithm based on sliding-mode for self-learning of mobile robots is discussed. Some control rules are built for the self-learning and obstacle avoidance of mobile robots, and the solving steps are also presented. Last, an experiment is designed to verify the proposed model and calculate the sliding- mode control for mobile robots. Some interesting conclusions and future work are indicated at the end of the paper.