Teleoperation-Driven and Keyframe-Based Generalizable Imitation Learning for Construction Robots

Author:

Li Yan1,Liu Songyang2ORCID,Wang Mengjun3,Li Shuai4ORCID,Tan Jindong5ORCID

Affiliation:

1. Postdoctoral Researcher, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996.

2. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996. ORCID: .

3. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996.

4. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996 (corresponding author). ORCID: .

5. Professor, Dept. of Mechanical, Aerospace, and Biomedical Engineering, Univ. of Tennessee, Knoxville, TN 37996. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Reference75 articles.

1. Abdolmaleki A. J. T. Springenberg Y. Tassa R. Munos N. Heess and M. Riedmiller. 2018. “Maximum a posteriori policy optimisation.” In Proc. 6th Int. Conf. on Learning Representations ICLR 2018. Appleton WI: International Conference on Learning Representations.

2. Robotic assembly of timber joints using reinforcement learning

3. A survey of inverse reinforcement learning: Challenges, methods and progress

4. Robotic architectural assembly with tactile skills: Simulation and optimization

5. Bharadhwaj H. A. Garg and F. Shkurti. 2020. “LEAF: Latent exploration along the frontier.” In Proc. IEEE Int. Conf. on Robotics and Automation (ICRA) 677–684. New York: IEEE.

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