Adaptive time horizon for on-line avoidance in dynamic environments

This paper addresses the issue of motion planning in dynamic environments using Velocity Obstacles. Specifically, we propose an adaptive time horizon to truncate the velocity obstacle so that its boundary closely, yet conservatively, approximates the boundary of the set of states from which collision is unavoidable. We wish to develop a representation such that any velocity vector that does not penetrate the velocity obstacle is safe, i.e. an avoidance maneuver exists, and any that does is not. Such clear partitioning between safe and unsafe velocities would allow safe planning with only one step look ahead, and can produce faster trajectories than the conservative trajectories produced when using an infinite time horizon. The computation of the adaptive time horizon is formulated as a minimum time problem, which is solved numerically for each static or moving obstacle. It is used in an on-line planner that generates locally time optimal trajectories to the goal. The planner is demonstrated for static and moving obstacles, and for on-line motion planning in a crowded dynamic environment.

[1]  Clayton W. Dodge Euclidean geometry and transformations , 2004 .

[2]  J. Kuffner,et al.  Improved Motion Planning Speed and Safety using Regions of Inevitable Collision , 2008 .

[3]  Jean-Claude Latombe,et al.  Randomized Kinodynamic Motion Planning with Moving Obstacles , 2002, Int. J. Robotics Res..

[4]  InMach Intelligente Maschinen,et al.  Reflective Navigation , 2005 .

[5]  Jeremy A. Salinger,et al.  A Unified Approach to Forward and Lane-Change Collision Warning for Driver Assistance and Situational Awareness , 2008 .

[6]  Thierry Fraichard,et al.  Safe motion planning in dynamic environments , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Hajime Asama,et al.  Inevitable collision states — a step towards safer robots? , 2004, Adv. Robotics.

[8]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[9]  Dinesh Manocha,et al.  Reciprocal Velocity Obstacles for real-time multi-agent navigation , 2008, 2008 IEEE International Conference on Robotics and Automation.

[10]  P. Fiorini,et al.  Motion planning in dynamic environments using the relative velocity paradigm , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[11]  Arthur E. Bryson,et al.  Applied Optimal Control , 1969 .

[12]  Christian Laugier,et al.  Motion Planning in Dynamic Environments , 2007 .

[13]  Zvi Shiller,et al.  Efficient and safe on-line motion planning in dynamic environments , 2009, 2009 IEEE International Conference on Robotics and Automation.

[14]  Christian Laugier,et al.  Navigation Among Moving Obstacles Using the NLVO: Principles and Applications to Intelligent Vehicles , 2005, Auton. Robots.