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Development of a Vision-Guided Shared-Control System for Assistive Robotic Manipulators

Dan Ding, Breelyn Kane Styler, Cheng-Shiu Chung, Alexander Houriet

2022Sensors13 citationsDOIOpen Access PDF

Abstract

Assistive robotic manipulators (ARMs) provide a potential solution to mitigating the difficulties and lost independence associated with manipulation deficits in individuals with upper-limb impairments. However, achieving efficient control of an ARM can be a challenge due to the multiple degrees of freedom (DoFs) of an ARM that need to be controlled. This study describes the development of a vision-guided shared-control (VGS) system and how it is applied to a multi-step drinking task. The VGS control allows the user to control the gross motion of the ARM via teleoperation and commands the ARM to autonomously perform fine manipulation. A bench-top test of the autonomous actions showed that success rates for different subtasks ranged from 80% to 100%. An evaluation with three test pilots showed that the overall task performance, in terms of success rate, task completion time, and joystick mode-switch frequency, was better with VGS than with teleoperation. Similar trends were observed with a case participant with a spinal cord injury. While his performance was better and he perceived a smaller workload with VGS, his perceived usability for VGS and teleoperation was similar. More work is needed to further improve and test VGS on participants with disabilities.

Topics & Concepts

JoystickTeleoperationUsabilityTask (project management)WorkloadComputer scienceSimulationRobotic armTest (biology)Control (management)Human–computer interactionEngineeringArtificial intelligenceBiologyPaleontologyOperating systemSystems engineeringGaze Tracking and Assistive TechnologyEEG and Brain-Computer InterfacesStroke Rehabilitation and Recovery
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