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A Shared Autonomy System for Precise and Efficient Remote Underwater Manipulation
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AI
DOI：10.1109/TRO.2024.3431830.png)
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Abstract
En 中文
Conventional underwater intervention operations using robotic vehicles require expert teleoperators and limit interaction with remote scientists. In this article, we present the shared autonomy for remote collaboration (SHARC) framework that enables novice operators to cooperatively conduct underwater sampling and manipulation tasks. With SHARC, operators can plan and complete manipulation tasks using natural language or hand gestures through a virtual reality (SHARC-VR) interface. The interface provides remote operators with a contextual 3-D scene understanding that is updated according to bandwidth availability. Evaluation of the SHARC framework through controlled lab experiments demonstrates that SHARC-VR enables novice operators to complete manipulation tasks in framerate-limited conditions (i.e., 0.1-0.5 frames per second) faster than expert pilots using a conventional topside controller. For both novice and expert users, the SHARC-VR interface also increases the task completion rate and improves sampling precision. The SHARC framework is readily extensible to other hardware architectures, including terrestrial and space systems.
Keywords:
Robots
Task analysis
Three-dimensional displays
Manipulators
Bandwidth
Cognitive load
Training
Shared autonomy
underwater manipulation
virtual reality (VR)
Journal
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10.5
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