Terrain discovery and navigation of a multi-articulated linear robot using map-seeking circuits

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.