Title :
SLQR suboptimal human-robot collaborative guidance and navigation for Autonomous Underwater Vehicles
Author :
Spencer, David A. ; Yue Wang
Author_Institution :
Dept. of Mech. Eng., Clemson Univ., Clemson, SC, USA
Abstract :
In this paper, a novel approach to the human-robot collaborative guidance and navigation of autonomous vehicles is proposed. The switched linear quadratic regulator (SLQR) is utilized as a method of determining when control of the autonomous vehicle should be switched from autonomous control to manual teleoperation or vice versa. This switching is determined by a quadratic cost function that takes into account both robot performance and human workload. A linearized model of an autonomous underwater vehicle (AUV) is derived and used for the purpose of simulations of the proposed controller. The performance of the proposed controller is also compared to that of a fully autonomous and fully manual control.
Keywords :
autonomous underwater vehicles; human-robot interaction; linear quadratic control; linearisation techniques; path planning; suboptimal control; switching systems (control); telerobotics; AUV; SLQR; autonomous underwater vehicles; fully autonomous control; fully manual control; human workload; linearized model; manual teleoperation; navigation; quadratic cost function; robot performance; suboptimal human-robot collaborative guidance; switched linear quadratic regulator; Collaboration; Human factors; Manuals; Navigation; Robots; Switches; Cooperative control; Human-Robot Collaboration; Optimal control; Switched systems;
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
DOI :
10.1109/ACC.2015.7171048