An integrated approach to real-time mobile robot control in partially known indoor environments

In this paper we present a motion control method for mobile robots in partially known indoor environments based on integration of focussed D* search algorithm and dynamic window local obstacle avoidance algorithm. While focussed D* generates global path, dynamic window local obstacle avoider generates the admissible robot trajectories that ensure safe robot motion. A simple and efficient procedure to the selection of appropriate motion commands based upon alignment of acquired trajectories and global geometric path is proposed. The initial a priori knowledge is used about the environment in the form of the occupancy grid map that is incrementally updated in runtime. The algorithms are verified both by simulation and experiments with a Pioneer 2DX mobile robot equipped with laser range finder.

I. Introduction

Indoor mobile robots should perform goal-directed tasks in cramped and unknown environments. Both global path planning and local reactive obstacle avoidance algorithms must be implemented in order to make a mobile robot with this capability. While a global path planning algorithm calculates optimal path to a specified goal, a reactive local obstacle avoidance module takes into account the unknown and changing characteristics of the environment based on the local sensory information.