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Robot Imitation Learning of Social Gestures with Self-Collision Avoidance Using a 3D Sensor
Tan Zhang1,2, Wing-Yue Louie3,4, Goldie Nejat5
1Autonomous Systems and Biomechatronics Lab, Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S3G8, Canada. tan.zhang@utoronto.ca.
Sensors (Basel, Switzerland)
|July 25, 2018
Summary
This study presents an imitation learning system enabling social robots to mimic human gestures. The system effectively avoids robot self-collisions during gesticulation, enhancing human-robot interaction.
Area of Science:
- Robotics
- Human-Robot Interaction
- Artificial Intelligence
Background:
- Social robots require sophisticated gesture generation for effective human interaction.
- Modeling complex, multi-jointed arm gestures poses challenges due to high-dimensional robot configurations.
- Imitation learning offers a method to teach robots gestures by observing human movements.
Purpose of the Study:
- To develop a novel imitation learning system for social robots capable of performing multi-jointed arm gestures.
- To integrate self-collision awareness and avoidance mechanisms into the robot's gesture execution.
- To evaluate the system's effectiveness in mimicking human gestures while ensuring robot safety.
Main Methods:
- Utilized imitation learning to map observed human arm movements to robot arm trajectories.
- Implemented a kinematical approach incorporating bounding volumes for self-collision detection.
- Employed a non-contact 3D sensor for capturing human teacher's gestures.
- Conducted experiments using a dual-arm social robot platform.
Main Results:
- The proposed system successfully enabled the social robot to mimic human gestures.
- The self-collision avoidance system effectively detected and prevented collisions during gesticulation.
- Demonstrated the feasibility of learning and executing complex gestures safely.
Conclusions:
- The novel imitation learning system enhances social robot capabilities for naturalistic human interaction.
- Robot self-collision awareness is crucial for safe and effective gesture performance.
- This approach provides a robust method for teaching robots complex motor skills through observation.
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