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Number of items: 10.

Gao, Yan, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861, Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X and Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902 2024. Efficient hierarchical reinforcement learning for mapless navigation with predictive neighbouring space scoring. IEEE Transactions on Automation Science and Engineering 21 (4) , pp. 5457-5472. 10.1109/TASE.2023.3312237
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X and Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902 2024. Accelerating multi-step sparse reward reinforcement learning. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023. Published in: Spezi, Emiliano and Bray, Michaela eds. Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press, pp. 86-90. 10.18573/conf1.u
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861, Lai, Yu-Kun ORCID: https://orcid.org/0000-0002-2094-5680 and Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902 2024. GAM: General Affordance-based Manipulation for contact-rich object disentangling tasks. Neurocomputing 578 , 127386. 10.1016/j.neucom.2024.127386
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861 and Lai, Yu-Kun ORCID: https://orcid.org/0000-0002-2094-5680 2023. Recent advances of deep robotic affordance learning: a reinforcement learning perspective. IEEE Transactions on Cognitive and Developmental Systems 15 (3) , pp. 1139-1149. 10.1109/TCDS.2023.3277288
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X 2023. Robotic object manipulation via hierarchical and affordance learning. PhD Thesis, Cardiff University.
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Zhang, Ting, Liu, Yang, Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Chen, Jingjing and Huang, Jiaming 2023. Home health care routing and scheduling in densely populated communities considering complex human behaviours. Computers and Industrial Engineering 182 , 109332. 10.1016/j.cie.2023.109332
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You, Yingchao, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X and Liu, Ying ORCID: https://orcid.org/0000-0001-9319-5940 2022. From human-human collaboration to human-robot collaboration: automated generation of assembly task knowledge model. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022), Bristol, UK, 1-3 Sept 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE, 10.1109/ICAC55051.2022.9911131
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861 and Lai, Yukun ORCID: https://orcid.org/0000-0002-2094-5680 2022. Abstract demonstrations and adaptive exploration for efficient and stable multi-step sparse reward reinforcement learning. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022), Bristol, United Kingdom, 1-3 September 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE, 10.1109/ICAC55051.2022.9911100
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861, Lai, Yu-kun ORCID: https://orcid.org/0000-0002-2094-5680, Wei, Changyun, Liu, Guoliang and Setchi, Rossitza ORCID: https://orcid.org/0000-0002-7207-6544 2022. Hierarchical reinforcement learning with universal policies for multi-step robotic manipulation. IEEE Transactions on Neural Networks and Learning Systems 33 (9) , pp. 4727-4741. 10.1109/TNNLS.2021.3059912
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Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861 and Lai, Yu-Kun ORCID: https://orcid.org/0000-0002-2094-5680 2021. An open-source multi-goal reinforcement learning environment for robotic manipulation with Pybullet. Presented at: 21st Towards Autonomous Robotic Systems Conference (TAROS 2021), Virtual, 8-10 September 2021. Published in: Fox, C., Gao, J., Ghalamzan Esfahani, A., Saaj, M., Hanheide, M. and Parsons, S. eds. Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science Springer, pp. 14-24.
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