Qi Liu

Orcid: 0000-0001-7485-6344

Affiliations:
  • Harbin Institute of Technology, Department of Control Science and Engineering, Shenzhen, China


According to our database1, Qi Liu authored at least 12 papers between 2020 and 2023.

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

Timeline

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Bibliography

2023
Distributional reinforcement learning with epistemic and aleatoric uncertainty estimation.
Inf. Sci., October, 2023

A fully distributed adaptive event-triggered control for output regulation of multi-agent systems with directed network.
Inf. Sci., May, 2023

2022
Autonomous vehicle self-localization in urban environments based on 3D curvature feature points - Monte Carlo localization.
Robotica, 2022

Battery Management for Warehouse Robots via Average-Reward Reinforcement Learning.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2022

Multi-Robot Real-time Game Strategy Learning based on Deep Reinforcement Learning.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2022

Decision Making for Autonomous Driving Via Multimodal Transformer and Deep Reinforcement Learning<sup>*</sup>.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2022

2021
A Deep Safe Reinforcement Learning Approach for Mapless Navigation.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2021

Towards Autonomous Driving Decision by Combining Self-attention and Deep Reinforcement Learning.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2021

Multi-agent Pathfinding with Local and Global Guidance.
Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2021

Efficient Power Grid Topology Control via Two-Stage Action Search.
Proceedings of the Intelligent Robotics and Applications - 14th International Conference, 2021

Exploration via Distributional Reinforcement Learning with Epistemic and Aleatoric Uncertainty Estimation.
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020
A 3D Simulation Environment and Navigation Approach for Robot Navigation via Deep Reinforcement Learning in Dense Pedestrian Environment.
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020


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