JOURNAL ARTICLE

Haptic Shared Control for an Underwater Robot

Hirokazu KonishiSyouta HIROSENorimitsu SakagamiTakahiro Wada

Year: 2019 Journal:   The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) Vol: 2019 (0)Pages: 2A2-H08   Publisher: Japan Society Mechanical Engineers

Abstract

Operation of remotely operated underwater robot (ROUV) is known to be difficult due to limited sensor information from the robot. We proposed to apply ta haptic shared control (HSC) approach, in which a human operator and an automation interact congruently in a perception-action cycle to perform a dynamic task by force inputs of both agents to a single operation input terminal., to the ROUV to increase operability of the robot.. We have prototyped an underwater robot with the HSC to investigate the effectiveness of our proposed method. Subjects were instructed to operate the underwater robot to the goal along a desired path line. An experimental factor was control method, which includes 1)HSC, 2)Fully manual, and 3)Fully automated. The subjects could partially see the desired path line and a goal visual target measured by a camera attached to the robot to operate the robot. In the HSC condition, the subjects could feel the force exerted on the joystick by the automatic control, which guided the robot to the desired path. Experimental results showed that HSC achieved lower mental workload than manual control. In addition, the HSC achieved high task performance by means of shorter task completion time than that in the manual control, while there were no significant difference in the tracking error between shared and manual control.

Keywords:
Joystick Robot Haptic technology Computer science Task (project management) Simulation Operability Robot control Workload Underwater Mobile robot Computer vision Artificial intelligence Engineering

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Topics

Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering
Teleoperation and Haptic Systems
Physical Sciences →  Engineering →  Mechanical Engineering
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
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