Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Hong, Jayden"'
Autor:
Karpichev, Yehor, Charter, Todd, Hong, Jayden, Enayati, Amir M. Soufi, Honari, Homayoun, Tamizi, Mehran Ghafarian, Najjaran, Homayoun
The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for customization. Human-ro
Externí odkaz:
http://arxiv.org/abs/2403.14597
Reinforcement learning (RL) for motion planning of multi-degree-of-freedom robots still suffers from low efficiency in terms of slow training speed and poor generalizability. In this paper, we propose a novel RL-based robot motion planning framework
Externí odkaz:
http://arxiv.org/abs/2307.16062
Finding an efficient way to adapt robot trajectory is a priority to improve overall performance of robots. One approach for trajectory planning is through transferring human-like skills to robots by Learning from Demonstrations (LfD). The human demon
Externí odkaz:
http://arxiv.org/abs/2304.05703
Autor:
Mukherjee, Debasmita1,2,3 (AUTHOR), Hong, Jayden2 (AUTHOR), Vats, Haripriya4 (AUTHOR), Bae, Sooyeon5 (AUTHOR), Najjaran, Homayoun2 (AUTHOR) najjaran@uvic.ca
Publikováno v:
User Modeling & User-Adapted Interaction. Sep2024, Vol. 34 Issue 4, p1327-1367. 41p.
Publikováno v:
IEEE Transactions on Robotics; 2024, Vol. 40 Issue: 1 p4733-4749, 17p