Autonomous Robots

, Volume 27, Issue 2, pp 93–103 | Cite as

A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot

  • Ruben Martinez-Cantin
  • Nando de Freitas
  • Eric Brochu
  • José Castellanos
  • Arnaud Doucet
Article

Abstract

We address the problem of online path planning for optimal sensing with a mobile robot. The objective of the robot is to learn the most about its pose and the environment given time constraints. We use a POMDP with a utility function that depends on the belief state to model the finite horizon planning problem. We replan as the robot progresses throughout the environment. The POMDP is high-dimensional, continuous, non-differentiable, nonlinear, non-Gaussian and must be solved in real-time. Most existing techniques for stochastic planning and reinforcement learning are therefore inapplicable. To solve this extremely complex problem, we propose a Bayesian optimization method that dynamically trades off exploration (minimizing uncertainty in unknown parts of the policy space) and exploitation (capitalizing on the current best solution). We demonstrate our approach with a visually-guide mobile robot. The solution proposed here is also applicable to other closely-related domains, including active vision, sequential experimental design, dynamic sensing and calibration with mobile sensors.

Keywords

Bayesian optimization Online path planning Sequential experimental design Attention and gaze planning Active vision Dynamic sensor networks Active learning Policy search Active SLAM Model predictive control Reinforcement learning 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Ruben Martinez-Cantin
    • 1
  • Nando de Freitas
    • 2
  • Eric Brochu
    • 2
  • José Castellanos
    • 3
  • Arnaud Doucet
    • 2
  1. 1.Institute for Systems and RoboticsInstituto Superior TécnicoLisboaPortugal
  2. 2.Department of Computer ScienceUniversity of British ColumbiaVancouverCanada
  3. 3.Department of Computer Science and System EngineeringUniversity of ZaragozaZaragozaSpain

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