Haoran Song

I am a Ph.D. candidate at the Robotics Institute, Hong Kong University of Science and Technology, where I work on robotics and machine learning under the supervision of Prof. Qifeng Chen and Prof. Michael Yu Wang.

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

Email / CV / Google Scholar / Github

Research

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. Since last year, I stepped on the journey towards autonomous driving and injected traditional planning ideas into learning-based methods. Now I'm dedicated to working on trajectory prediction and motion planning for autonomous driving. My first-authored works are listed below.

Ongoing projects: I'm currently developing robust and interpretable algorithms on multi-modal prediction under urban scenarios.

	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 / arXiv / 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 / arXiv / bibtex
	Herding by Caging Haoran Song, Anastasiia Varava, Danica Kragic, Michael Yu Wang, Florian T. Pokorny, Kaiyu Hang Under review at Autonomous Robots (AURO), 2019 Apply computational geometry and topology in planning a set of mobile robots to address the interesting 'herding' task.
	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, Cover Article in March 2019 Drones that perch like birds could go on much longer flights! Media Reports: 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

Other Projects

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)

Modified from Dr. Jon Barron's design of the website.