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Proceedings Paper

Grid-based framework for sensorial data integration in mobile robots
Author(s): Augusto Ferreira da Silva; P. Menezes; Jorge Miranda Dias; Helder Araujo
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Paper Abstract

This article presents a method to combine data from two sensorial modalities, a stereoscopic vision based sensor and a ring of ultrasonic sensors, in a grid based framework for obstacle detection and avoidance with mobile robots. The sensors' data is combined using Dempster-Shafer theory. This theory allows the combination of multiple sensorial data sources in a way that they are mutually enhanced and validated. A connectionist grid is used to support these operations and the environment modeling. Each grid node maps a configuration in a discrete subset of the robot's configuration space. The process used to obtain obstacle presence information from the stereoscopic setup and ultrasonic sensors is explained in detail. Detected obstacles result in sets of restricted configurations. The grid dynamic behavior allows the iterative computation of a repulsive potential field, which rises in the vicinity of the restricted configurations. As new information is collected by the sensors during the robot's motion so new configurations are marked as restrict and the potential field changes accordingly. Since this process occurs in real time, the computed potential field can be used to navigate the robot avoiding the detected obstacles. Experimental results are presented to support the used sensor models, the integration procedure and the control strategy.

Paper Details

Date Published: 22 September 1997
PDF: 12 pages
Proc. SPIE 3209, Sensor Fusion and Decentralized Control in Autonomous Robotic Systems, (22 September 1997); doi: 10.1117/12.287635
Show Author Affiliations
Augusto Ferreira da Silva, Univ. de Coimbra (Portugal)
P. Menezes, Univ. de Coimbra (Portugal)
Jorge Miranda Dias, Univ. de Coimbra (Portugal)
Helder Araujo, Univ. de Coimbra (Portugal)

Published in SPIE Proceedings Vol. 3209:
Sensor Fusion and Decentralized Control in Autonomous Robotic Systems
Paul S. Schenker; Gerard T. McKee, Editor(s)

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