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Intentional Control for Planetary Rover SRR

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Intentional behavior is a basic property of intelligence, and it incorporates the cyclic operation of prediction, testing by action, sensing, perceiving and assimilating the experienced features. Intentional neurodynamic principles are applied for on-line processing of multisensory inputs and for the generation of dynamic behavior using the SRR (Sample Return Rover) platform at the indoor facility of the Planetary Robotics Laboratory, Jet Propulsion Laboratory. The studied sensory modalities include CMOS camera vision, orientation based on an internal motion unit and accelerometer signals. The control architecture employs a biologically inspired dynamic neural network operating on the principle of chaotic neural dynamics manifesting intentionality in the style of mammalian brains. Learning is based on Hebbian rules coupled with reinforcement. The central issue of this work is to study how the developed control system builds associations between the sensory modalities to achieve robust autonomous action selection. The proposed system builds such associations in a self-organized way and it is called Self-Organized Development of Autonomous Adaptive Systems (SODAS). This system operates autonomously, without the need for human intervention, which is a potentially very beneficial feature in challenging environments, such as encountered in space explorations at remote planetary environments. The experiments illustrate obstacle avoidance combined with goal-oriented navigation by the SRR robot using SODAS control principles.
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Document Type: Research Article

Affiliations: 1: Computational NeuroDynamics Laboratory, 373 Dunn, University of Memphis, Memphis, TN 38152, USA 2: Jet Propulsion Laboratory, California Institute of Technology, Planetary Robotics Laboratory, MS 82-105, 4800 Oak Grove Drive, Pasadena, CA 91109, USA 3: Applied Physics Laboratory, Johns Hopkins University, 11100 Johns Hopkins Road, Laurel, MD 20723, USA 4: Division of Neurobiology, MCB, University of California at Berkeley, 101 Donner, Berkeley, CA 94720, USA

Publication date: 2008-10-01

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