Skip to Main content Skip to Navigation
Conference papers

Lambda-Field: a continuous counterpart of the bayesian occupancy grid for risk assessment

Abstract : In a context of autonomous robots, one of the most important task is to ensure the safety of the robot and its surrounding. Most of the time, the risk of navigation is simply said to be the probability of collision. This notion of risk is not well defined in the literature, especially when dealing with occupancy grids. The Bayesian occupancy grid is the most used method to deal with complex environments. However, this is not fitted to compute the risk along a path by its discrete nature, hence giving poor results. In this article, we present a new way to store the occupancy of the environment that allows the computation of risk for a given path. We then define the risk as the force of collision that would occur for a given obstacle. Using this framework, we are able to generate navigation paths ensuring the safety of the robot.
Document type :
Conference papers
Complete list of metadata
Contributor : Migration Irstea Publications Connect in order to contact the contributor
Submitted on : Saturday, May 16, 2020 - 6:53:58 PM
Last modification on : Wednesday, February 24, 2021 - 4:16:03 PM


  • HAL Id : hal-02609985, version 1
  • IRSTEA : PUB00063859
  • WOS : 000544658400018


Johann Laconte, C. Debain, Chapuis Roland, F. Pomerleau, R. Aufrere. Lambda-Field: a continuous counterpart of the bayesian occupancy grid for risk assessment. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2019, Macau, China. ⟨hal-02609985⟩



Record views