Nov 15, 2023 · A novel GRF-GMM method is proposed for learning from demonstrations and avoiding the obstacle which is not presented in original demonstrations.
Nov 20, 2023 · Learning from demonstrations (LfD) provides a convenient pattern to teach robot to gain skills without mechanically programming.
Learning from demonstrations (LfD) provides a convenient pattern to teach robot to gain skills without mechanically programming. As an LfD approach, ...
To address these problems, this paper presents a novel method based on Gaussian repulsive field-Gaussian mixture model (GRF-GMM) for obstacle avoidance by ...
This paper presents a novel optimised approach to improve Gaussian clusters then further GMM/GMR so that LfD enabled cobots can carry out a variety of complex ...
The main idea is to imitate the obstacle avoidance mechanism of human beings, in which humans learn to make a decision based on the sensor information obtained ...
Publications that cite this publication. GRF-GMM: A Trajectory Optimization Framework for Obstacle Avoidance in Learning from Demonstration. Bin Ye, Peng Yu ...
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GRF-GMM: A Trajectory Optimization Framework for Obstacle Avoidance in Learning from Demonstration. Bin Ye, Peng Yu, Cong Hu, Binbin Qiu, Ning Tan. https ...
【会议论文】GRF-GMM: A Trajectory Optimization Framework for Obstacle Avoidance in Learning from Demonstration NSTL国家科技图书文献中心. 作者：. Bin Ye | Peng ...
Abstract—Learning motions from human demonstrations provides an intuitive way for non-expert users to teach tasks to robots.