ROJan 31, 2019

Characterizing Input Methods for Human-to-robot Demonstrations

arXiv:1902.00084v118 citations
Originality Incremental advance
AI Analysis

This work addresses the problem of designing effective demonstration methods for robotics applications, but it is incremental as it builds on existing paradigms without a major breakthrough.

The paper tackled the lack of systematic study in input methods for human-to-robot demonstrations by characterizing existing methods and introducing instrumented tongs, with a user study showing that tongs provide high-quality demonstrations and positive user experience.

Human demonstrations are important in a range of robotics applications, and are created with a variety of input methods. However, the design space for these input methods has not been extensively studied. In this paper, focusing on demonstrations of hand-scale object manipulation tasks to robot arms with two-finger grippers, we identify distinct usage paradigms in robotics that utilize human-to-robot demonstrations, extract abstract features that form a design space for input methods, and characterize existing input methods as well as a novel input method that we introduce, the instrumented tongs. We detail the design specifications for our method and present a user study that compares it against three common input methods: free-hand manipulation, kinesthetic guidance, and teleoperation. Study results show that instrumented tongs provide high quality demonstrations and a positive experience for the demonstrator while offering good correspondence to the target robot.

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