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Passively Safe Partial Motion Planning for Mobile Robots with Limited Field-of-Views in Unknown Dynamic Environments

Sara Bouraine 1 Thierry Fraichard 2, * Ouahiba Azouaoui 1 Hassen Salhi 3
* Corresponding author
2 PRIMA - Perception, recognition and integration for observation of activity
Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble , CNRS - Centre National de la Recherche Scientifique : UMR5217
Abstract : This paper addresses the problem of planning the motion of a mobile robot with a limited sensory field-of-view in an unknown dynamic environment. In such a situation, the upper-bounded planning time prevents from computing a complete motion to the goal, partial motion planning is in order. Besides the presence of moving obstacles whose future behaviour is unknown precludes \textit{absolute motion safety} (in the sense that no collision will ever take place whatever happens) is impossible to guarantee. The stance taken herein is to settle for a weaker level of motion safety called \textit{passive motion safety}: it guarantees that, if a collision takes place, the robot will be at rest. The primary contribution of this paper is {\passivepmp}, a partial motion planner enforcing passive motion safety. {\passivepmp} periodically computes a passively safe partial trajectory designed to drive the robot towards its goal state. Passive motion safety is handled using a variant of the Inevitable Collision State (ICS) concept called \textit{Braking ICS}, {\ie} states such that, whatever the future braking trajectory of the robot, a collision occurs before it is at rest. Simulation results demonstrate how {\passivepmp} operates and handles limited sensory field-of-views, occlusions and moving obstacles with unknown future behaviour. More importantly, {\passivepmp} is provably passively safe.
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Submitted on : Friday, July 4, 2014 - 4:05:10 PM
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Sara Bouraine, Thierry Fraichard, Ouahiba Azouaoui, Hassen Salhi. Passively Safe Partial Motion Planning for Mobile Robots with Limited Field-of-Views in Unknown Dynamic Environments. IEEE Int. Conf. on Robotics and Automation (ICRA), Jun 2014, Hong Kong, Hong Kong SAR China. ⟨hal-01018463⟩



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