Paper
9 May 2006 Terrain discovery and navigation of a multi-articulated linear robot using map-seeking circuits
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Abstract
A significant challenge in robotics is providing a robot with the ability to sense its environment and then autonomously move while accommodating obstacles. The DARPA Grand Challenge, one of the most visible examples, set the goal of driving a vehicle autonomously for over a hundred miles avoiding obstacles along a predetermined path. Map-Seeking Circuits have shown their biomimetic capability in both vision and inverse kinematics and here we demonstrate their potential usefulness for intelligent exploration of unknown terrain using a multi-articulated linear robot. A robot that could handle any degree of terrain complexity would be useful for exploring inaccessible crowded spaces such as rubble piles in emergency situations, patrolling/intelligence gathering in tough terrain, tunnel exploration, and possibly even planetary exploration. Here we simulate autonomous exploratory navigation by an interaction of terrain discovery using the multi-articulated linear robot to build a local terrain map and exploitation of that growing terrain map to solve the propulsion problem of the robot.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ross K. Snider and David W. Arathorn "Terrain discovery and navigation of a multi-articulated linear robot using map-seeking circuits", Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 62290H (9 May 2006); https://doi.org/10.1117/12.663721
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Cited by 5 scholarly publications.
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KEYWORDS
Superposition

Robotics

Clouds

Kinematics

Neurons

Brain mapping

Brain

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