Honghu Xue, M. Sc.
Doktorand
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Ratzeburger Allee 160 23562 Lübeck Gebäude 64, Raum 89 (EG)
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Short Biography
Honghu Xue received his M.Sc. in Embedded Systems Engineering at Albert-Ludwigs-University of Freiburg with the study focus on Reinforcement Learning, Machine Learning and AI. From March.2019, he is a Ph.D. student at the institute "Robotics and Cognitive Systems".
Research Interestes
- (Deep) Reinforcement Learning (Model-based RL, Sample-efficient RL, RL on hard problems featuring long time horizon)
- Efficient Exploration Strategy
- Online Model Learning in RL via Deep Learning (sequential prediction problem and Probabilistic model characterizing transition stochasticity)
Membership
Publikationen
2023
| , , , , , and , Deep Reinforcement Learning for Autonomous Navigation in Intralogistics, 2023 |
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2022
| , , , , , , and , Cerebellar transcranial current stimulation-an intraindividual comparison of different techniques (2022), in: Frontiers Neuroscience |
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| , , , , and , End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments, The 2022 IEEE-RAS International Conference on Humanoid Robots, 2022 |
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| , , , , and , Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics (2022), in: Applied Sciences special issue "Intelligent Robotics", 12:6(3153) |
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2021
| , , , , , and , Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience (2021), in: Advanced Intelligent Systems |
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| , , , , and , Using Probabilistic Movement Primitives in analyzing human motion differences under Transcranial Current Stimulation (2021), in: Frontiers Robot. AI - Humanoid Robotics |
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2020
| , , , , and , ACNMP: Flexible Skill Formation with Learning from Demonstration and Reinforcement Learning via Representation Sharing, Virtual Conference, Conference on Robot Learning (CoRL), 2020 |
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| , , , and , Parameter Optimization for Loop Closure Detection in Closed Environments (2020), in: Workshop Paper at the International Conference on Intelligent Robots and Systems (IROS)(8) |
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| , , , , , and , Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks, Berlin, Germany, Proceedings of International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI), 2020 |
[DOI] [Bib|RIS] [URL] |