Yongle Luo

Orcid: 0000-0001-9933-3611

According to our database1, Yongle Luo authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Reinforcement Learning with Decoupled State Representation for Robot Manipulations.
Neural Process. Lett., October, 2024

A Novel Trajectory-Based Ball Spin Estimation Method for Table Tennis Robot.
IEEE Trans. Ind. Electron., August, 2024

Dyna-style Model-based reinforcement learning with Model-Free Policy Optimization.
Knowl. Based Syst., 2024

Constraint-aware Online Joint-Space Motion Planning for Robotic Table Tennis.
Proceedings of the 2024 4th International Conference on Robotics and Control Engineering, 2024

2023
Relay Hindsight Experience Replay: Self-guided continual reinforcement learning for sequential object manipulation tasks with sparse rewards.
Neurocomputing, November, 2023

D2SR: Transferring Dense Reward Function to Sparse by Network Resetting.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2023

Reinforcement Learning with Goal Relabeling and Dynamic Model for Robotic Tasks.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2023

SIRL: Self-Imitation Reinforcement Learning for Single-step Hitting Tasks.
Proceedings of the International Conference on Advanced Robotics and Mechatronics, 2023

2022
Relay Hindsight Experience Replay: Continual Reinforcement Learning for Robot Manipulation Tasks with Sparse Rewards.
CoRR, 2022

Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty.
Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2022

2021
Calibration-Free Monocular Vision-Based Robot Manipulations With Occlusion Awareness.
IEEE Access, 2021

2020
Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty.
CoRR, 2020


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