Navigation and Measurement Control in Complex Environment

Abstract

The navigation system of mobile robot should have the capability of environment cognition, action decision, motion control, and state monitoring. This paper presents a design of mobile robot control architecture and a survey about the navigation control method. In vision based mapping domain, our research put emphasis on the hybrid of model and appearance based approach. An environmental model of mobile robots is built with an improved Voronoi Diagram method. This method embodies the network structure of the environment-free area with fewer nodes, so the complexity of path planning is reduced largely. Hybrid navigation strategy composed of deliberative planning and local optimization in unknown environment is studied. An improved D* algorithm for deliberative planning in complex situation is proposed for avoiding local minima trap through searching a path from leave point. The reverse D* algorithm can decrease the calculation largely compared with the traditional D* algorithm in unknown environment.