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- Title
Human–Robot Interaction Using Learning from Demonstrations and a Wearable Glove with Multiple Sensors.
- Authors
Singh, Rajmeet; Mozaffari, Saeed; Akhshik, Masoud; Ahamed, Mohammed Jalal; Rondeau-Gagné, Simon; Alirezaee, Shahpour
- 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.
- Subjects
HUMAN-robot interaction; SURGICAL gloves; MACHINE learning; MULTISENSOR data fusion; DETECTORS; GLOVES; PRESSURE sensors; MOTION detectors
- Publication
Sensors (14248220), 2023, Vol 23, Issue 24, p9780
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s23249780