Constraint-based semi-autonomy for unmanned ground vehicles using local sensing

Sterling J. Anderson; Sisir B. Karumanchi; Bryan Johnson; Victor Perlin; Mitchell Rohde; Karl Iagnemma

doi:10.1117/12.919265

25 May 2012 Constraint-based semi-autonomy for unmanned ground vehicles using local sensing

Sterling J. Anderson, Sisir B. Karumanchi, Bryan Johnson, Victor Perlin, Mitchell Rohde, Karl Iagnemma

Proceedings Volume 8387, Unmanned Systems Technology XIV; 83870K (2012) https://doi.org/10.1117/12.919265
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Teleoperated vehicles are playing an increasingly important role in a variety of military functions. While advantageous in many respects over their manned counterparts, these vehicles also pose unique challenges when it comes to safely avoiding obstacles. Not only must operators cope with difficulties inherent to the manned driving task, but they must also perform many of the same functions with a restricted field of view, limited depth perception, potentially disorienting camera viewpoints, and significant time delays. In this work, a constraint-based method for enhancing operator performance by seamlessly coordinating human and controller commands is presented. This method uses onboard LIDAR sensing to identify environmental hazards, designs a collision-free path homotopy traversing that environment, and coordinates the control commands of a driver and an onboard controller to ensure that the vehicle trajectory remains within a safe homotopy. This system's performance is demonstrated via off-road teleoperation of a Kawasaki Mule in an open field among obstacles. In these tests, the system safely avoids collisions and maintains vehicle stability even in the presence of "routine" operator error, loss of operator attention, and complete loss of communications.

Citation Download Citation

Sterling J. Anderson, Sisir B. Karumanchi, Bryan Johnson, Victor Perlin, Mitchell Rohde, and Karl Iagnemma "Constraint-based semi-autonomy for unmanned ground vehicles using local sensing", Proc. SPIE 8387, Unmanned Systems Technology XIV, 83870K (25 May 2012); https://doi.org/10.1117/12.919265

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