This paper describes a multisensor data-fusion system for driving an autonomous earthwork vehicle operating in a sanitary landfill. The system acquires data from a set of ultrasonic sensors, a laser range finder, and several charge-coupled device cameras, and produces as output alarms that indicate potential dangerous situations, e.g., the presence of fixed or mobile obstacles in the vehicle working area. The proposed system adds to the vehicle important functionalities such as to avoid terrain holes or down slopes or to discriminate between heaps of waste to be compacted and other man-made obstacles. Data fusion allows one to increase the system's reliability and to compensate for the inaccuracies and limited operating ranges of individual sensors. Experimental results show the system's functioning both under normal operational conditions and in the presence of dangerous situations. Moreover, the performances of the system in bad environmental situations (e.g., rain, low lighting) have been evaluated.

Multisensor data fusion for autonomous vehicle navigation in risky environments

C. S. Regazzoni;
2002-01-01

Abstract

This paper describes a multisensor data-fusion system for driving an autonomous earthwork vehicle operating in a sanitary landfill. The system acquires data from a set of ultrasonic sensors, a laser range finder, and several charge-coupled device cameras, and produces as output alarms that indicate potential dangerous situations, e.g., the presence of fixed or mobile obstacles in the vehicle working area. The proposed system adds to the vehicle important functionalities such as to avoid terrain holes or down slopes or to discriminate between heaps of waste to be compacted and other man-made obstacles. Data fusion allows one to increase the system's reliability and to compensate for the inaccuracies and limited operating ranges of individual sensors. Experimental results show the system's functioning both under normal operational conditions and in the presence of dangerous situations. Moreover, the performances of the system in bad environmental situations (e.g., rain, low lighting) have been evaluated.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1104929
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