Distributed Sensing and Prediction of Obstacle Motions for Mobile Robot Motion Planning

Abstract

This work recommends an architecture and its fundamental components for motion planning for mobile robots in dynamic environments. An adaptive behavior to typical motion patterns of people is essential for robots to be accepted in crowded environments. This adaptation is achieved by a global and distributed sensing system to detect obstacle motions and model motion behavior. This article focuses on the detection, the modeling and the prediction of obstacle motion behavior. The model consists of a dynamic Bayesian network. The topology of the network is a geometric graph