Adaptive Intelligence for Robot Navigation Efficiency with a Deep-Reinforcement-Learning-Based Cyber-Physical System
Published in 2024 International Conference on Computing in Civil Engineering (i3CE), 2024
This research develops an adaptive intelligence framework that leverages deep reinforcement learning to optimize robot navigation efficiency in construction environments. The cyber-physical system integrates real-time sensing, decision-making, and control to enable more efficient robotic operations.
Recommended citation: Zhao, X., Ren, T., and Jebelli, H. (2024). “Adaptive Intelligence for Robot Navigation Efficiency with a Deep-Reinforcement-Learning-Based Cyber-Physical System.” 2024 International Conference on Computing in Civil Engineering (i3CE), Pittsburgh, Pennsylvania, U.S. (Accepted).
Recommended citation: Zhao, X., Ren, T., and Jebelli, H. (2024). "Adaptive Intelligence for Robot Navigation Efficiency with a Deep-Reinforcement-Learning-Based Cyber-Physical System." 2024 International Conference on Computing in Civil Engineering (i3CE), Pittsburgh, Pennsylvania, U.S. (Accepted).
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