no code implementations • 17 Sep 2023 • Wenxing Liu, Hanlin Niu, Robert Skilton, Joaquin Carrasco
This paper proposes a self-supervised vision-based DRL method that allows robots to pick and place objects effectively and efficiently when directly transferring a training model from simulation to the real world.
no code implementations • 26 Feb 2023 • Wenxing Liu, Hanlin Niu, Wei Pan, Guido Herrmann, Joaquin Carrasco
Sim-and-real training is a promising alternative to sim-to-real training for robot manipulations.
1 code implementation • 21 Feb 2021 • Hanlin Niu, Ze Ji, Farshad Arvin, Barry Lennox, Hujun Yin, Joaquin Carrasco
An efficient training strategy is proposed to allow a robot to learn from both human experience data and self-exploratory data.
no code implementations • 21 Feb 2021 • Hanlin Niu, Ze Ji, Zihang Zhu, Hujun Yin, Joaquin Carrasco
This paper presents the development of a control system for vision-guided pick-and-place tasks using a robot arm equipped with a 3D camera.