Abstract
Autonomous mobile robots capable of intelligent behavior must operate with minimal human interaction, have the capability to utilize local resources, and routinely make closed-loop decisions in real-time based on sensor data inputs. One of the bottlenecks in achieving this is an often computationally intensive perception process. In this paper, we discuss a class of cognitive sensor devices capable of intelligent perception that can facilitate intelligent behavior. The primary emphasis is on achieving safe mobile guidance for planetary exploration by distributing some of the perception functionality to self-contained sensors. An example cognitive sensor, called the traversability sensor, is presented, which consists of a camera and embedded processor coupled with an intelligent visual perception algorithm. The sensor determines local terrain traversability in natural outdoor environments and, accordingly, directs movement of a mobile robot toward the safest visible terrain area in a self-contained fashion, placing minimal burden on the main processor. A cognitive sensor design approach is presented and a traversability sensor prototype is described.
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Howard, A., Tunstel, E. (2006). A Self-Contained Traversability Sensor for Safe Mobile Robot Guidance in Unknown Terrain. In: Abraham, A., de Baets, B., Köppen, M., Nickolay, B. (eds) Applied Soft Computing Technologies: The Challenge of Complexity. Advances in Soft Computing, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31662-0_56
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DOI: https://doi.org/10.1007/3-540-31662-0_56
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