Projects per year
Abstract
Sim-and-real training is a promising alternative to sim-to-real training for robot manipulations. However, the current sim-and-real training is neither efficient, i.e., slow con-vergence to the optimal policy, nor effective, i.e., sizeable real-world robot data. Given limited time and hardware budgets, the performance of sim-and-real training is not satisfactory. In this paper, we propose a Consensus-based Sim-And-Real deep reinforcement learning algorithm (CSAR) for manipulator pick-and-place tasks, which shows comparable performance in both sim-and- real worlds. In this algorithm, we train the agents in simulators and the real world to get the optimal policies for both sim-and-real worlds. We found two interesting phenomenons: (1) Best policy in simulation is not the best for sim-and-real training. (2) The more simulation agents, the better sim-and-real training. The experimental video is available at: https://youtu.be/mcHJtNIsTEQ.
Original language | English |
---|---|
Title of host publication | Proceedings - ICRA 2023 |
Subtitle of host publication | IEEE International Conference on Robotics and Automation |
Publisher | IEEE |
Pages | 3911-3917 |
Number of pages | 7 |
ISBN (Electronic) | 9798350323658 |
DOIs | |
Publication status | Published - 2023 |
Event | 2023 IEEE International Conference on Robotics and Automation, ICRA 2023 - London, United Kingdom Duration: 29 May 2023 → 2 Jun 2023 |
Publication series
Name | Proceedings - IEEE International Conference on Robotics and Automation |
---|---|
Volume | 2023-May |
ISSN (Print) | 1050-4729 |
Conference
Conference | 2023 IEEE International Conference on Robotics and Automation, ICRA 2023 |
---|---|
Country/Territory | United Kingdom |
City | London |
Period | 29/05/23 → 2/06/23 |
Fingerprint
Dive into the research topics of 'Sim-and-Real Reinforcement Learning for Manipulation: A Consensus-based Approach'. Together they form a unique fingerprint.Projects
- 1 Active
-
MCAIF: Centre for AI Fundamentals
Kaski, S. (PI), Alvarez, M. (Researcher), Pan, W. (Researcher), Mu, T. (Researcher), Rivasplata, O. (PI), Sun, M. (PI), Mukherjee, A. (PI), Caprio, M. (PI), Sonee, A. (Researcher), Leroy, A. (Researcher), Wang, J. (Researcher), Lee, J. (Researcher), Parakkal Unni, M. (Researcher), Sloman, S. (Researcher), Menary, S. (Researcher), Quilter, T. (Researcher), Hosseinzadeh, A. (PGR student), Mousa, A. (PGR student), Glover, E. (PGR student), Das, A. (PGR student), DURSUN, F. (PGR student), Zhu, H. (PGR student), Abdi, H. (PGR student), Dandago, K. (PGR student), Piriyajitakonkij, M. (PGR student), Rachman, R. (PGR student), Shi, X. (PGR student), Keany, T. (PGR student), Liu, X. (PGR student), Jiang, Y. (PGR student), Wan, Z. (PGR student), Harrison, M. (Support team), Machado, M. (Support team), Hartford, J. (PI), Kangin, D. (Researcher), Harikumar, H. (PI), Dubey, M. (PI), Parakkal Unni, M. (PI), Dash, S. P. (PGR student), Mi, X. (PGR student) & Barlas, Y. (PGR student)
1/10/21 → 30/09/26
Project: Research