4.7 Article

A Gesture-Based Natural Human-Robot Interaction Interface With Unrestricted Force Feedback

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2022.3149109

关键词

Robots; Force; Coils; Human-robot interaction; Force feedback; Tracking; Task analysis; Electromagnetic force; force feedback; human-robot interaction; Kalman filters; multi-sensors

资金

  1. Key-Area Research and Development Program of Guangdong Province [2020B010166006]
  2. National Natural Science Foundation of China [62173176, 61973126, 61863028, 81660299, 61503177]
  3. Innovation Team of the Modern Agriculture Industry Technology System in Guangdong Province [2019KJ139]
  4. Chinese Institute of Electronics (CIE)Tencent Robotics X Rhino-Bird Focused Research Program
  5. Science and Technology Department of Jiangxi Province of China [20204ABC03A39]

向作者/读者索取更多资源

This article presents a novel gesture-based natural human-robot interaction interface, which integrates a markerless gesture tracking system and an unrestricted electromagnetic force feedback mechanism. The proposed interface allows the operator to control the robot naturally and efficiently without any markers, while providing high-precision operation accuracy. Experimental results demonstrate the suitability of this interface for high-precision human-robot interactive tasks.
This article presents a novel gesture-based natural human-robot interaction interface, which integrates a markerless gesture tracking system and an unrestricted electromagnetic force feedback mechanism. In this proposed interface, a markerless gesture tracking system is developed to relate the motion of the operator's hand to the robot manipulator so that the operator can naturally and friendly control the robot without any markers. More importantly, this interface uses a new unrestricted electromagnetic force feedback mechanism to avoid the friction, hysteresis, and other nonlinear influence in the conventional actuation dynamics. The interface makes the operator obtain the effective force immersion of the robot. Therefore, the proposed interface can provide the promising operation accuracy for the operator. To effectively regulate the electric currents of coils and provide accurate force feedback, the broad learning system (BLS) is introduced in this unrestricted electromagnetic force feedback mechanism. In addition, two interval Kalman filters (IKFs) are applied to estimate the position and orientation of the operator's hand, respectively, improving the measurement accuracy of the proposed interface. Experimental results show that the proposed interface is suitable for high-precision human-robot interactive tasks and enables the operator to focus on the tasks and operate dual robot manipulator, which provides natural and efficient human-robot interaction.

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