Dynamic sensor action selection with Bayesian decision analysis

Steen Kristensen; Volker Hansen; Konstantin Kondak

doi:10.1117/12.327000

9 October 1998 Dynamic sensor action selection with Bayesian decision analysis

Steen Kristensen, Volker Hansen, Konstantin Kondak

Proceedings Volume 3523, Sensor Fusion and Decentralized Control in Robotic Systems; (1998) https://doi.org/10.1117/12.327000
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

The aim of this work is to create a framework for the dynamic planning of sensor actions for an autonomous mobile robot. The framework uses Bayesian decision analysis, i.e., a decision-theoretic method, to evaluate possible sensor actions and selecting the most appropriate ones given the available sensors and what is currently known about the state of the world. Since sensing changes the knowledge of the system and since the current state of the robot (task, position, etc.) determines what knowledge is relevant, the evaluation and selection of sensing actions is an on-going process that effectively determines the behavior of the robot. The framework has been implemented on a real mobile robot and has been proven to be able to control in real-time the sensor actions of the system. In current work we are investigating methods to reduce or automatically generate the necessary model information needed by the decision- theoretic method to select the appropriate sensor actions.

Citation Download Citation

Steen Kristensen, Volker Hansen, and Konstantin Kondak "Dynamic sensor action selection with Bayesian decision analysis", Proc. SPIE 3523, Sensor Fusion and Decentralized Control in Robotic Systems, (9 October 1998); https://doi.org/10.1117/12.327000

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