Abstract
Vehicle navigation in dynamic environments is a challenging task, especially when the motion of the obstacles populating the environment is unknown beforehand and is updated at runtime. Traditional motion planning approaches are too slow to be applied in real-time to this problem, whereas reactive navigation methods have generally a too short look-ahead horizon. Recently, iterative planning has emerged as a promising approach, however, it does not explicitly take into account the movements of the obstacles.
This paper presents a real-time motion planning approach, based on the concept of the Non-Linear Vobst (NLVO) (Shiller et al., 2001). Given a predicted environment, the NLVO models the set of velocities which lead to collisions with static and moving obstacles, and an estimation of the times-to-collision. At each controller iteration, an iterative A* motion planner evaluates the potential moves of the robot, based on the computed NLVO and the traveling time. Previous search results are reused to both minimize computation and maintain the global coherence of the solutions.
We first review the concept of the NLVO, and then present the iterative planner. The planner is then applied to vehicle navigation and demonstrated in a complex traffic scenario.
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Frédéric Large is a member of the French National Consortium on road automation, namely LaRA (“La Route Automatisée”), in the eMotion (formely known as Sharp) research project-team at INRIA (French National Institute for Research on Computer Science and Control). He holds an engineer degree in artificial intelligence (1998) and a master and his Ph.D. in computer science (2003) from the University of Savoie in the Rhône-Alpes (France). Dr. Large works on modelling and reasonning for mobile service-robots and intelligent vehicles. In particular, he specialises on autonomous navigation in environments shared by moving obstacles whose future behaviour is uncertain.
Christian Laugier is Research Director at INRIA (French National Institute for Research on Computer Science and Control), and leader of the robotics project-team at INRIA Rhône-Alpes since 1984. He received the Ph.D. and “State Doctor” degrees in Computer Science from Grenoble University (France) in 1976, and 1987 respectively. His current research interests mainly lies in the areas of Motion Autonomy, Intelligent Vehicles, Decisional Processes, and Virtual Reality. In 1997, he was awarded the Nakamura Prize for his contribution to the advancement of the technology on Intelligent Robots and Systems. Pr. Christian Laugier is a member of several scientific national and international committees (several French scientific committees, Adcom of IROS, Adcom of the EURON European Network, etc.), and he is regularly involved in the organizing committees of the major international conferences in Robotics (e.g. IEEE ICRA and IEEE/RSJ IROS). In addition to his research and teaching activities, he participated in the start-up of four industrial companies in the fields of Robotics, Computer Vision, and Computer Graphics.
Zvi Shiller is a Professor, founder and head of the Department of Mechanical Engineering-Mechatronics at the College of Judea and Samaria in Ariel, Israel. He received the B.Sc. (‘76) from Tel Aviv University, and the M.Sc. (‘84) and Sc.D. (‘87) from the Massachusetts Institute of Technology, all in Mechanical Engineering. Before joining the College of Judea and Samaria in 2001, he served fourteen years on the faculty of the Department of Mechanical and Aerospace Engineering at UCLA. Professor Shiller’s current research interests include trajectory planning, multi-robot coordination, navigation of autonomous off-road vehicles and active safety of intelligent road vehicles.
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Large, F., Laugier, C. & Shiller, Z. Navigation Among Moving Obstacles Using the NLVO: Principles and Applications to Intelligent Vehicles. Auton Robot 19, 159–171 (2005). https://doi.org/10.1007/s10514-005-0610-8
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DOI: https://doi.org/10.1007/s10514-005-0610-8