Human-Robot Interaction Using Learning from Demonstrations and a Wearable Glove with Multiple Sensors.

Journal: Sensors (Basel, Switzerland)
Published Date: Dec 12, 2023

Abstract

Human-robot interaction is of the utmost importance as it enables seamless collaboration and communication between humans and robots, leading to enhanced productivity and efficiency. It involves gathering data from humans, transmitting the data to a robot for execution, and providing feedback to the human. To perform complex tasks, such as robotic grasping and manipulation, which require both human intelligence and robotic capabilities, effective interaction modes are required. To address this issue, we use a wearable glove to collect relevant data from a human demonstrator for improved human-robot interaction. Accelerometer, pressure, and flexi sensors were embedded in the wearable glove to measure motion and force information for handling objects of different sizes, materials, and conditions. A machine learning algorithm is proposed to recognize grasp orientation and position, based on the multi-sensor fusion method.

Authors

  • Rajmeet Singh
    Mechanical, Automotive, and Material Engineering Department, University of Windsor, Windsor, ON N9B 3P4, Canada.
  • Saeed Mozaffari
    Mechanical, Automotive, and Material Engineering Department, University of Windsor, Windsor, ON N9B 3P4, Canada.
  • Masoud Akhshik
    Mechanical, Automotive, and Material Engineering Department, University of Windsor, Windsor, ON N9B 3P4, Canada.
  • Mohammed Jalal Ahamed
    Mechanical, Automotive, and Material Engineering Department, University of Windsor, Windsor, ON N9B 3P4, Canada.
  • Simon Rondeau-Gagné
    Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, Canada.
  • Shahpour Alirezaee
    Mechanical, Automotive, and Material Engineering Department, University of Windsor, Windsor, ON N9B 3P4, Canada.

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