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A gripper-like exoskeleton design for robot grasping demonstration

Dai, Hengtai; Lu, Zhenyu; He, Mengyuan; Yang, Chenguang

A gripper-like exoskeleton design for robot grasping demonstration Thumbnail


Hengtai Dai

Zhenyu Lu

Mengyuan He


Learning from demonstration (LfD) is a practical method for transferring skill knowledge from a human demonstrator to a robot. Several studies have shown the effectiveness of LfD in robotic grasping tasks to improve the success rate of grasping and to accelerate the development of new robotic grasping tasks. A well-designed demonstration device can effectively represent human grasping motion to transfer grasping skills to robots. In this paper, an improved gripper-like exoskeleton with a data collection system is proposed. First, we present the mechatronic details of the exoskeleton and its motion-tracking system, considering the manipulation flexibility and data acquisition requirements. We then present the capabilities of the device and its data collection system, which collects the position, pose and displacement of the gripper on the exoskeleton. The collected data is further processed by the data acquisition and processing software. Next, we describe the principles of Gaussian mixture model (GMM) and Gaussian mixture regression (GMR) in robot skill learning, which are used to transfer the raw data from demonstrations to robot motions. In the experiment, an optimized trajectory was learned from multiple demonstrations and reproduced on a robot. The results show that the GMR complemented with GMM is able to learn a smooth trajectory from demonstration trajectories with noise.

Journal Article Type Article
Acceptance Date Jan 6, 2023
Online Publication Date Jan 12, 2023
Publication Date Jan 12, 2023
Deposit Date Jan 14, 2023
Publicly Available Date Jan 16, 2023
Journal Actuators
Electronic ISSN 2076-0825
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 12
Issue 1
Pages 39
Keywords Control and Optimization; Control and Systems Engineering; learning from demonstration (LfD); hand exoskeleton; robotic grasping; trajectory learning; Gaussian mixture models (GMM); Gaussian mixture regression (GMR)
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