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.
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