Haoran Song

I received the Ph.D. degree from Robotics Institute, Hong Kong University of Science and Technology in 2021, where I worked on robotics and machine learning under the supervision of Prof. Michael Yu Wang and Prof. Qifeng Chen.

I was a visiting scholar at the Robotics, Perception and Learning Lab, KTH Royal Institute of Technology in 2018, working with Prof. Danica Kragic. Before that, I obtained the Bachelor degree in Flight Vehicle Design and Engineering from Harbin Institute of Technology in 2016.

Email / CV / Google Scholar / Github

Experience

Currently I'm working at Huawei IAS BU, focusing on developing prediction & planning algorithms for Autonomous Driving.

My research lies in motion forecasting and planning. Early in my Ph.D. study, much of my research is about robotics planning under physical interaction. After that, I stepped on the journey towards autonomous driving and injected traditional planning ideas into learning-based methods.

My first-authored works are listed below.

	Learning to Predict Vehicle Trajectories with Model-based Planning Haoran Song, Di Luan, Wenchao Ding, Michael Yu Wang, Qifeng Chen Conference on Robot Learning (CoRL 2021), London, UK Make accurate, feasible, and robust trajectory prediction by a novel architecture with a model-based generator and a learning-based evaluator. project page / paper / bibtex
	PiP: Planning-informed Trajectory Prediction for Autonomous Driving Haoran Song, Wenchao Ding, Yuxuan Chen, Shaojie Shen, Michael Yu Wang, Qifeng Chen European Conference on Computer Vision (ECCV 2020), Glasgow, Scotland, UK Inform the multi-agent future prediction with ego vehicle's planning in a novel planning-prediction-coupled pipeline. project page / paper / bibtex
	Multi-Object Rearrangement with Monte Carlo Tree Search: A Case Study on Planar Nonprehensile Sorting Haoran Song, Joshua A. Haustein, Weihao Yuan, Kaiyu Hang, Michael Yu Wang, Danica Kragic, Johannes A. Stork IEEE International Conference on Intelligent Robots and Systems (IROS 2020), Las Vegas, USA Learn policy from MCTS and employ it to reinforce MCTS, to address sorting task under multi-contact physics. project page / paper / bibtex
	Herding by Caging: A Formation-based Motion Planning Framework for Guiding Mobile Agents Haoran Song, Anastasiia Varava, Oleksandr Kravchenko, Danica Kragic, Michael Yu Wang, Florian T. Pokorny, Kaiyu Hang Autonomous Robots (AURO), 2021 Apply computational geometry and topology in planning a set of mobile robots to address the interesting 'herding' task. paper / video / bibtex
	Perching and resting - A paradigm for UAV maneuvering with modularized landing gears Kaiyu Hang, Ximin Lyu, Haoran Song, Johannes A Stork, Aaron M Dollar, Danica Kragic, Fu Zhang (* denotes equal contribution) Science Robotics, 2019 (Cover article) Drones that perch like birds could go on much longer flights! with reported by MIT Technology Review, Nature Electronics, National Public Radio, etc. paper / video / bibtex
	Fingertip surface optimization for robust grasping on contact primitives Haoran Song, Michael Yu Wang, Kaiyu Hang IEEE Robotics and Automation Letters (RA-L), 2018 & IEEE International Conference on Robotics and Automation (ICRA 2018), Brisbane, Australia Rethink grasp planning from geometry matching rather than traditional point contact modeling. paper / bibtex

Others

These include other projects and issued patents.

	Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation Weihao Yuan, Kaiyu Hang, Haoran Song, Danica Kragic, Michael Y. Wang, Johannes A. Stork IEEE International Conference on Robotics and Automation (ICRA 2019), Montreal, Canada paper / bibtex / code
	Robotic fingertip design and grasping on contact primitives Kaiyu Hang, Haoran Song US Patent App. 16/192,169, 2019 patent info / bibtex

Service

Reviewer for IEEE Transactions on Robotics (T-RO)
Reviewer for IEEE Robotics and Automation Letters (RA-L)
Reviewer for IEEE International Conference on Robotics and Automation (ICRA)
Reviewer for IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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