Intelligent Sensor-Based Navigation and Control of Mobile Robot in a Partially Known Environment

Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In this paper, a new approach is proposed for navigation and control of a wheeled mobile robot in a partially known environment. A collision-free path is calculated using an efficient neural motion planner. An additional fuzzy logic based navigation strategy is developed to adjust the moving information in the cases when the mobile robot encounters unexpected obstacles. The output of the navigation level is transformed into a time indexed data sequence which is fed into a tracking controller that takes into account the complete dynamics of the mobile base. The locomotion control structure is based on the integration of a kinematic controller and an adaptive fuzzy-net torque controller.