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Collision-free navigation based on people tracking algorithm with biped walking model

This paper investigates a collision-free navigation algorithm for a mobile robot to work in daily environment which includes multiple walking people. The proposed algorithm consists of two main parts: recognizing walking people and collision-free path planning. For the recognition of randomly changing human walking motion, a people tracking method using laser range finder (LRF) is utilized. Robust people tracking could be achieved by embedding a new biped model with a walking frequency tracker, which can estimate the frequency of human walking motion and generate it continuously even in the case of no measurement owing to occlusion. For the other part, collision-free path planning, an iterative forecast and planning method with the concept of configuration space including space and time is employed. The position and velocity of walking people, given from people tracking algorithm, are exploited in path planning part as the information of obstacles that the robot have to avoid. The proposed method has been implemented on a real robot. It is also demonstrated with some experiments the tracking of multiple walking humans and robot navigation in indoor environment.