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Human–robot collaboration has become very important in the industrial areas including the manufacturing domain, as the fixed programming of robot activities is becoming outdated. The main reason for expecting collaboration between humans and robots is due to the dynamic nature of the tasks occurring besides its preprogrammed tasks. However, traditional industrial robots that are controlled by preprogrammed control codes are rigid and they cannot support the emerging needs of human–robot collaboration. To address this, in recent years, many ways of collaboration and communication between humans and robots have been evolving. In this article, two methods, i.e., motion sensor-based hand tracking IR-based sensors and computer vision-based hand tacking are implemented and analyzed in detail for their performance and accuracy.

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Integrating Hand Gesture Tracking with Physical and Digital Twins of Robotic Arm

  • 会议论文

  • 发表日期：

    2025年

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  • Ojas Jain,
  • Krishnaiah Jallu

摘要

Human–robot collaboration has become very important in the industrial areas including the manufacturing domain, as the fixed programming of robot activities is becoming outdated. The main reason for expecting collaboration between humans and robots is due to the dynamic nature of the tasks occurring besides its preprogrammed tasks. However, traditional industrial robots that are controlled by preprogrammed control codes are rigid and they cannot support the emerging needs of human–robot collaboration. To address this, in recent years, many ways of collaboration and communication between humans and robots have been evolving. In this article, two methods, i.e., motion sensor-based hand tracking IR-based sensors and computer vision-based hand tacking are implemented and analyzed in detail for their performance and accuracy.