Research


The following are projects mostly from my time at the Boston Dynamics AI Institute .

Sumo: Dynamic and Generalizable Whole-Body Loco-Manipulation
John Z. Zhang, Maks Sorokin, Jan Brüdigam, Brandon Hung, Stephen Phillips, Dmitry Yershov, Farzad Niroui, Tong Zhao, Leonor Fermoselle, Xinghao Zhu, Chao Cao, Duy Ta, Tao Pang, Jiuguang Wang, Preston Culbertson, Zachary Manchester, Simon Le Cleac'h
To appear in IEEE Transactions on Robot Learning, 2026
paper | website | code
Equivariant Diffusion Policy for Sample-Efficient Robotic Manipulation
Dian Wang, Stephen Hart, David Surovik, Tarik Kelestemur, Haojie Huang, Haibo Zhao, Mark Yeatman, Xupeng Zhu, Boce Hu, Mingxi Jia, Jiuguang Wang, Robin Walters, Robert Platt
International Journal of Robotics Research, February 2026
CoRL 2024 Outstanding Paper Award Finalist
paper | website | code
SAGA: Open-World Mobile Manipulation via Structured Affordance Grounding
Kuan Fang, Yuxin Chen, Xinghao Zhu, Farzad Niroui, Lingfeng Sun, Jiuguang Wang
IEEE Robotics and Automation Letters, vol. 11, no. 9, pp. 10361-10368, September 2026
paper | website | code (coming soon)
CuriousBot: Interactive Mobile Exploration via Actionable 3D Relational Object Graph
Yixuan Wang, Leonor Fermoselle, Tarik Kelestemur, Jiuguang Wang, Yunzhu Li
IEEE Robotics and Automation Letters, vol. 11, no. 4, pp. 4993-5000, April 2026
paper | website | code (coming soon)
From Pixels to Predicates: Learning Symbolic World Models Via Pretrained VLMs
Ashay Athalye, Nishanth Kumar, Tom Silver, Yichao Liang, Jiuguang Wang, Tomás Lozano-Pérez, Leslie Pack Kaelbling
IEEE Robotics and Automation Letters, vol. 11, no. 4, pp. 4002-4009, April 2026
paper | website | code
Generative Models From and for Sampling-Based MPC: A Bootstrapped Approach for Adaptive Contact-Rich Manipulation
Lara Brudermüller, Brandon Hung, Xinghao Zhu, Jiuguang Wang, Nick Hawes, Preston Culbertson, Simon Le Cleac'h
IEEE Robotics and Automation Letters, vol. 11, no. 3, pp. 3478-3485, March 2026
paper | website (coming soon) | code (coming soon)
Judo: A User-Friendly Open-Source Package for Sampling-Based Model Predictive Control
Albert H. Li, Brandon Hung, Jan Brüdigam, Aaron D. Ames, Jiuguang Wang, Simon Le Cleac'h, Preston Culbertson
IEEE International Conference on Robotics and Automation (ICRA), Vienna, Austria, June 2026
paper | website | code
ASHiTA: Automatic Scene-grounded HIerarchical Task Analysis
Yun Chang, Leonor Fermoselle, Duy Ta, Bernadette Bucher, Luca Carlone, Jiuguang Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, pp. 29458-29468, June 2025
paper | code (coming soon)
Physics-Driven Data Generation for Contact-Rich Manipulation via Trajectory Optimization
Lujie Yang, H. J. Terry Suh, Tong Zhao, Bernhard Paus Graesdal, Tarik Kelestemur, Jiuguang Wang, Tao Pang, Russ Tedrake
Robotics: Science and Systems (RSS), Los Angeles, CA, USA, June 2025
paper | website | code (coming soon)
Versatile Loco-Manipulation through Flexible Interlimb Coordination
Xinghao Zhu, Yuxin Chen, Lingfeng Sun, Farzad Niroui, Simon Le Cleac'h, Jiuguang Wang, Kuan Fang
Conference on Robot Learning (CoRL), Seoul, Korea, PMLR vol. 305, pp. 610-632, September 2025
paper | website | code
Should We Learn Contact-Rich Manipulation Policies from Sampling-Based Planners?
Huaijiang Zhu, Tong Zhao, Xinpei Ni, Jiuguang Wang, Kuan Fang, Ludovic Righetti, Tao Pang
IEEE Robotics and Automation Letters, vol. 10, no. 6, pp. 6248-6255, June 2025
2025 IEEE Robotics and Automation Letters Best Paper Award
paper
Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans?
Yuki Shirai, Tong Zhao, H. J. Terry Suh, Huaijiang Zhu, Xinpei Ni, Jiuguang Wang, Max Simchowitz, Tao Pang
IEEE International Conference on Robotics and Automation (ICRA), Atlanta, GA, USA, pp. 11926-11932, May 2025
paper
EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy
Xiaoyi Cai, Siddharth Ancha, Lakshay Sharma, Philip R. Osteen, Bernadette Bucher, Stephen Phillips, Jiuguang Wang, Michael Everett, Nicholas Roy, Jonathan P. How
IEEE Transactions on Robotics, vol. 40, pp. 3756-3777, 2024
paper | website | code
VLFM: Vision-Language Frontier Maps for Zero-Shot Semantic Navigation
Naoki Yokoyama, Sehoon Ha, Dhruv Batra, Jiuguang Wang, Bernadette Bucher
IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, pp. 42-48, May 2024
Best Paper Award in Cognitive Robotics
paper | website | code
GenDP: 3D Semantic Fields for Category-Level Generalizable Diffusion Policy
Yixuan Wang, Guang Yin, Binghao Huang, Tarik Kelestemur, Jiuguang Wang, Yunzhu Li
Conference on Robot Learning (CoRL), Munich, Germany, PMLR vol. 270, pp. 4866-4878, November 2024
paper | website | code
Jacta: A Versatile Planner for Learning Dexterous and Whole-body Manipulation
Jan Brüdigam, Ali Adeeb Abbas, Maks Sorokin, Kuan Fang, Brandon Hung, Maya Guru, Stefan Georg Sosnowski, Jiuguang Wang, Sandra Hirche, Simon Le Cleac'h
Conference on Robot Learning (CoRL), Munich, Germany, PMLR vol. 270, pp. 994-1020, November 2024
paper | website | code
Continuously Improving Mobile Manipulation with Autonomous Real-World RL
Russell Mendonca, Emmanuel Panov, Bernadette Bucher, Jiuguang Wang, Deepak Pathak
Conference on Robot Learning (CoRL), Munich, Germany, PMLR vol. 270, pp. 5204-5219, November 2024
paper | website
Equivariant Diffusion Policy
Dian Wang, Stephen Hart, David Surovik, Tarik Kelestemur, Haojie Huang, Haibo Zhao, Mark Yeatman, Jiuguang Wang, Robin Walters, Robert Platt
Conference on Robot Learning (CoRL), Munich, Germany, PMLR vol. 270, pp. 48-69, November 2024
CoRL 2024 Outstanding Paper Award Finalist
paper | website | code