Bio

I am a Post Doctoral researcher working with Prof. Shuran Song at Stanford Electric Engineering. Prior to joining Stanford, I spent three years as an Applied Scientist at Amazon Robotics working on the Stow project. I obtained my PhD and MS degrees from the Robotics Institute at Carnegie Mellon University, obtained BoE from the department of Automation at Tsinghua University. I had also spent time interning at Toyota Research Institute and MIT.

I work on robotic manipulation. I am currently interested in the intersection of data-driven visual motor policies and model based compliance control.

Stanford Advisors

Contact

  • Academic
    yifanhou@stanford.edu
    University - Scholar Department: Electrical Engineering Position: Postdoctoral Scholar

Additional Info

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Lab Affiliations

All Publications

  • SimPLE, a visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects SCIENCE ROBOTICS Bauza, M., Bronars, A., Hou, Y., Taylor, I., Chavan-Dafle, N., Rodriguez, A. 2024; 9 (91): eadi8808

    Abstract

    Existing robotic systems have a tension between generality and precision. Deployed solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single task, lacking "precise generalization," or the ability to solve many tasks without compromising on precision. This paper explores solutions for precise and general pick and place. In precise pick and place, or kitting, the robot transforms an unstructured arrangement of objects into an organized arrangement, which can facilitate further manipulation. We propose SimPLE (Simulation to Pick Localize and placE) as a solution to precise pick and place. SimPLE learns to pick, regrasp, and place objects given the object's computer-aided design model and no prior experience. We developed three main components: task-aware grasping, visuotactile perception, and regrasp planning. Task-aware grasping computes affordances of grasps that are stable, observable, and favorable to placing. The visuotactile perception model relies on matching real observations against a set of simulated ones through supervised learning to estimate a distribution of likely object poses. Last, we computed a multistep pick-and-place plan by solving a shortest-path problem on a graph of hand-to-hand regrasps. On a dual-arm robot equipped with visuotactile sensing, SimPLE demonstrated pick and place of 15 diverse objects. The objects spanned a wide range of shapes, and SimPLE achieved successful placements into structured arrangements with 1-mm clearance more than 90% of the time for six objects and more than 80% of the time for 11 objects.

    View details for DOI 10.1126/scirobotics.adi8808

    View details for Web of Science ID 001255119900005

    View details for PubMedID 38924419

  • Extrinsic Dexterous Manipulation with a Direct-drive Hand: A Case Study Gupta, A., Mao, Y., Bhatia, A., Cheng, X., King, J., Hou, Y., Mason, M. T., IEEE IEEE. 2022: 4660-4667

    View details for DOI 10.1109/IROS47612.2022.9981569

    View details for Web of Science ID 000908368203065

  • Manipulation with Suction Cups Using External Contacts Cheng, X., Hou, Y., Mason, M. T., Asfour, T., Yoshida, E., Park, J., Christensen, H., Khatib, O. SPRINGER INTERNATIONAL PUBLISHING AG. 2022: 692-708

    View details for DOI 10.1007/978-3-030-95459-8_42

    View details for Web of Science ID 000771723700042

  • Contact Mode Guided Motion Planning for Quasidynamic Dexterous Manipulation in 3D Cheng, X., Huang, E., Hou, Y., Mason, M. T., IEEE IEEE. 2022: 2730-2736

    View details for DOI 10.1109/ICRA46639.2022.9811872

    View details for Web of Science ID 000941265701120

  • An Efficient Closed-Form Method for Optimal Hybrid Force-Velocity Control Hou, Y., Mason, M. T., IEEE IEEE. 2021: 11125-11131

    View details for DOI 10.1109/ICRA48506.2021.9561426

    View details for Web of Science ID 000771405403090

  • Contact Mode Guided Sampling-Based Planning for Quasistatic Dexterous Manipulation in 2D Cheng, X., Huang, E., Hou, Y., Mason, M. T., IEEE IEEE. 2021: 6520-6526

    View details for DOI 10.1109/ICRA48506.2021.9560766

    View details for Web of Science ID 000765738804126

  • Robust Planar Dynamic Pivoting by Regulating Inertial and Grip Forces Workshop on Algorithmic Foundations of Robotics Hou, Y., Jia, Z., Mason, M. T. 2020

    View details for DOI 10.1007/978-3-030-43089-4_30

  • Manipulation with Shared Grasping Hou, Y., Jia, Z., Mason, M. T., Toussaint, M., Bicchi, A., Hermans, T. MIT PRESS. 2020

    View details for Web of Science ID 000570976900086

  • Pushing revisited: Differential flatness, trajectory planning, and stabilization INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH Zhou, J., Hou, Y., Mason, M. T. 2019; 38 (12-13): 1477-1489

    View details for DOI 10.1177/0278364919872532

    View details for Web of Science ID 000487162600001

  • Criteria for Maintaining Desired Contacts for Quasi-Static Systems Hou, Y., Mason, M. T., IEEE IEEE. 2019: 6555-6561

    View details for DOI 10.1109/iros40897.2019.8968592

    View details for Web of Science ID 000544658405027

  • Robust Execution of Contact-Rich Motion Plans by Hybrid Force-Velocity Control Hou, Y., Mason, M. T., IEEE, Howard, A., Althoefer, K., Arai, F., Arrichiello, F., Caputo, B., Castellanos, J., Hauser, K., Isler, Kim, J., Liu, H., Oh, P., Santos, Scaramuzza, D., Ude, A., Voyles, R., Yamane, K., Okamura, A. IEEE. 2019: 1933-1939

    View details for DOI 10.1109/icra.2019.8794366

    View details for Web of Science ID 000494942301072

  • Fast Planning for 3D Any-Pose-Reorienting Using Pivoting IEEE International Conference on Robotics and Automation (ICRA) Hou, Y., Jia, Z., Mason, M. T. 2018

    View details for DOI 10.1109/ICRA.2018.8462834

  • Follow My Step: A Framework for Biped Robots to Imitate Human Walking Hou, Y., Zhao, M., IEEE IEEE. 2014: 2471-2476

    View details for Web of Science ID 000380399500414

https://orcid.org/0000-0001-8446-941X