High-Speed Autonomous Navigation with Motion Prediction for Unknown Moving Obstacles and Motion Prediction

Vehicle navigation in dynamic environments is an important challenge, especially when the motion of the objects populating the environment is unknown. Traditional motion planning approaches are too slow to be applied in realtime to this domain, hence, new techniques are needed. Recently, iterative planning has emerged as a promising approach. Nevertheless, existing iterative methods do not provide a way to estimate the future behaviour of moving obstacles and use the resulting estimates in trajectory computation. This paper presents an iterative planning approach that addresses these two issues. It consists of two complementary methods: 1) a motion prediction method which learns typical behaviours of objects in a given environment. 2) an iterative motion planning technique based on the concept of Velocity Obstacles. Acknowledgements — This work has been partially supported by a Conacyt scolarship. We also want to thank the support of the CNRS Robea ParkNav, the Lafmi NavDyn and the european Cybercars projects. The autors would like to thank Prof. Zvi Shiller for his contribution to this work.