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Proceedings Paper

Autonomous synthesis of goal-oriented behaviors for planetary robotic sampling
Author(s): Sukhan Lee; Paul S. Schenker
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Paper Abstract

An intelligent robotic architecture that autonomously synthesizes goal-oriented behaviors, while connecting sensing and action in real-time, is presented with applications to loosely defined planetary sampling missions. By the goal-oriented behaviors, we mean sequences of actions generated from automatic task monitoring and replanning toward set goals in the presence of uncertainties as well as errors and faults. This architecture is composed of perception and action nets interconnected in closed loops. The perception net, represented as a hierarchy of features that can be extracted from physical as well as logical sensors, manages uncertainties with sensor fusion, sensor planning, and consistency maintenance. The action net, represented as a hierarchy of state transition in which all the possible system behaviors are embedded, generates robust and fault-tolerant system behaviors with on-line adaptive task monitoring and replanning. The proposed intelligent robotic architecture is significant for autonomous planetary robotic sampling -- and related robotic tasks in unstructured environments -- that require robust and fault tolerant behaviors due to expected uncertainties as well as errors in sensing, actuation, and environmental constraints. We use a typical Mars planetary sampling scenario to evaluate the proposed architecture; autonomous soil science where a robot arm trenches soil to examine and deposit soil samples to lander based science instrumentation.

Paper Details

Date Published: 30 October 1996
PDF: 13 pages
Proc. SPIE 2905, Sensor Fusion and Distributed Robotic Agents, (30 October 1996); doi: 10.1117/12.256337
Show Author Affiliations
Sukhan Lee, Jet Propulsion Lab. and Univ. of Southern California (United States)
Paul S. Schenker, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 2905:
Sensor Fusion and Distributed Robotic Agents
Paul S. Schenker; Gerard T. McKee, Editor(s)

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