WCBM Workshop

About

WCBM @ RSS 2026

Motivation

Humanoid robots have long held promise to be seamlessly deployed in our daily lives. Despite the rapid progress in humanoid robots' hardware (e.g. Boston Dynamics Atlas, Tesla Optimus, Unitree H1, 1X Neo, Agility Digit), their software is fully or partially hand-designed for specific tasks. The goal of Whole-body Control and Bimanual Manipulation (WCBM) workshop is to provide a platform for roboticists and machine learning researchers to discuss the past achievements of whole-body control and manipulation as well as future research directions on this topic, especially on the problem of enabling autonomous humanoid robots. We invited a group of speakers who are world-renowned experts to present their work on whole-body control for humanoid robots and bimanual robotic systems. We also want to provide researchers with the opportunity to present their latest research by accepting workshop papers. We will review and select the best submissions for spotlight talks and interactive poster presentations. We have also planned guided panel discussions to encourage debate among the invited speakers and workshop participants. In the discussion, we would like to contrast the viewpoints of machine learning researchers and roboticists on the past and future of this research topic.

If you have any questions, feel free to contact us.

Program

Workshop schedule

🚪CB07.02.025 (Room 25, 2nd floor, UTS Building "7")

Zoom link

Time	Event
09:00 - 09:05	Opening Remark
09:05 - 09:30	Joohyung Kim (UIUC)
09:30 - 09:55	Siyuan Huang (BIGAI)
09:55 - 10:20	Tony Zhao (Sunday Robotics)
10:20 - 10:45	Karen Liu (Stanford)
10:45 - 11:15	Coffee Break and Poster Session (CB07.02.020, CB07.02.015)
11:15 - 11:40	Spotlight Talks
11:40 - 12:10	Panel Discussion
12:10 - 12:30	Closing Remarks

Talks

Invited Speakers

Joohyung Kim is an Associate Professor of ECE (Electrical and Computer Engineering) and MechSE (Mechanical Science & Engineering), and the director of KIMLAB (Kinetic Intelligent Machine LAB) at University of Illinois, Urbana-Champaign. His research focuses on design and control for humanoid robots, system for motion learning in robot hardware, and safe human-robot interaction. He received BSE and Ph.D. degrees in Electrical Engineering and Computer Science (EECS) from Seoul National University, Korea, in 2001 and 2012. He was with Disney Research as a Research Scientist from 2013 to 2019. Prior to joining Disney, he was a postdoctoral fellow in the Robotics Institute at Carnegie Mellon University for DARPA Robotics Challenge in 2013. From 2009 to 2012, he was a Research Staff Member in Samsung Advanced Institute of Technology and Samsung Electronics, Korea, developing biped walking controllers for humanoid robots.

Siyuan Huang is a Research Scientist at Beijing Institute for General Artificial Intelligence (BIGAI), directing the Center of Embodied AI and Robotics. He received his Ph.D. from the Department of Statistics at the University of California, Los Angeles (UCLA). His research aims to build a general robot capable of understanding and interacting with 3D environments like humans. His research has received multiple awards including the best paper award of CoRL2025 and several workshop best papers.

Tony Zhao is the co-founder and CEO of Sunday Robotics. He previously worked on ALOHA and ACT at Stanford before dropping out.

Karen Liu is a professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. Liu's research interests are in computer graphics and robotics, including physics-based animation, character animation, optimal control, reinforcement learning, and computational biomechanics. She developed computational approaches to modeling realistic and natural human movements, learning complex control policies for humanoids and assistive robots, and advancing fundamental numerical simulation and optimal control algorithms. The algorithms and software developed in her lab have fostered interdisciplinary collaboration with researchers in robotics, computer graphics, mechanical engineering, biomechanics, neuroscience, and biology. Liu received a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and was named Young Innovators Under 35 by Technology Review. In 2012, Liu received the ACM SIGGRAPH Significant New Researcher Award for her contribution in the field of computer graphics.

Posters

Workshop Posters

Check out our workshop papers at OpenReview: https://openreview.net/group?id=roboticsfoundation.org/RSS/2026/Workshop/WCBM

Poster Spotlights:

Learning Versatile Humanoid Manipulation with Touch Dreaming. Yaru Niu, Zhenlong Fang, Binghong Chen, Shuai Zhou, Revanth Krishna Senthilkumaran, Hao Zhang, Bingqing Chen, Chen Qiu, Eric H. Tseng, Jonathan Francis, Ding Zhao
Counterfactual Video Generation for Humanoid Loco-Manipulation. Zihan Wang, Zhen Wu, Pieter Abbeel, Rocky Duan, Jitendra Malik, Carmelo Sferrazza, Karen Liu, Guanya Shi, Angjoo Kanazawa
OmniXtreme: Breaking the Generality Barrier in High-Dynamic Humanoid Control. Yunshen Wang, Shaohang Zhu, Peiyuan Zhi, Yuhan Li, Jiaxin Li, Yong-Lu Li, Yuchen Xiao, Xingxing Wang, Baoxiong Jia, Siyuan Huang
Sumo: Dynamic and Generalizable Whole-Body Loco-Manipulation. John Zhang
TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model. Anqi Li, Yuxin Chen, Zhaobo Li, Zhuo Cao, Junli Ren, Masayoshi Tomizuka, Dhruv Shah

Posters:

CoorDex: Coordinating Body and Hand Priors for Continuous Dexterous Humanoid Loco-Manipulation. Sikai Li, Shuning Li, Zhenyu Wei, Yunchao Yao, Chenran Li, Mingyu Ding
Can We Tune Humanoid Behavior Foundation Models for Dynamic and Contact-Rich Tasks? Mengjie Zhao, Yuxin Chen, Shaoting Zhu, Yu Hong, Yunshen Wang, Yicheng Liu, Baijun Ye, Xiaoyu Tian, Baoxiong Jia, Hang Zhao, Siyuan Huang, Masayoshi Tomizuka
Learning Visual Humanoid Loco-Manipulation Policies from Simulated Experiences. Omar Rayyan, Zhi Li, Max Argus, Yuxin Jiang, Chang Yu, Chenfanfu Jiang, Yuchen Cui
Mini Pi Plus: A Compact Modular Humanoid Platform for Onboard Whole-Body Learning and Deployment. Xiaobai Zhang, wang xu, Xiongshi Xu, Tang Zhanhui, Huiying Lai, Yuhao Niu, Shihong Yao, Ziwen Zhuang, Hanya Huang, Chengwei Song, Chen zujin, Mi Liu, Qiabo Wang, Zixiang Long
TeCH: Temporal Distance Modeling via Contrastive Representation Learning for Humanoid Whole-Body Control. Yitang Li
WARP: Whole-Body Retargeting for Learning from Offline Human Demonstrations. Zhenyang Chen, Chuizheng Kong, Chuye Zhang, Yuanshao Yang, Lawrence Y. Zhu, Shreyas Kousik, Danfei Xu
Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning. Shuo Cheng, Chuye Zhang, Alfred Cueva, Caelan Reed Garrett, Ajay Mandlekar, Danfei Xu
PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations. Yang Zhang, Jiangyuan Zhao, Chenyou Fan, Fangzheng YAN, Tian Li, Haitong Tang, Xuaner Wu, Qizhen Weng, Weinan Zhang, Xiu Li, Chi Zhang, Chenjia Bai, Xuelong Li
Perceptive Behavior Foundation Model: Adapting Human Motion Priors to Robot-Centric Terrain. Zifan Wang, Yizhao Li, Teli Ma, Qiang Zhang, Yudong Fan, Hao Xu, Shuo Yang, Junwei Liang
Test-Time Scaling for Executable Whole-Body Humanoid Motion from Language. Jianuo Cao, Yuxin Chen, Yuzhen Song, Masayoshi Tomizuka, Chenran Li, Thomas Tian
UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms. Yufei Jia, Zhanxiang Cao, Mingrui Yu, Heng Zhang, Shenyu Chen, Dixuan Jiang, Meng Li, Xiaofan Li, Yiyang Liu, junzhe wu, Zheng Li, xilin fang, Ting-Yu Tsui, Shengcheng Fu, Haoyang Li, Anqi Wang, Zifan Wang, Dongjie Zhu, Chenyu Cao, Zhenbiao Huang et al. (31 additional authors not shown)
Robot Skill Puzzles: Decentralized Skill Priors for Humanoid–Environment Interaction. Zhiyang Dou, Jintao Lu, Boyang Yu, Zeyu Cao, Cheng Lin, Yuan Liu, Taku Komura
ResMimic: From General Motion Tracking to Humanoid Whole-body Loco-Manipulation via Residual Learning. Siheng Zhao, Yanjie Ze, Yue Wang, Karen Liu, Pieter Abbeel, Guanya Shi, Rocky Duan
How Visible Are Silent Failures in Bimanual Manipulation? An Observability Study of False-Success Detection in Simulated ALOHA Episodes. Aarav Bedi
MSK-Bench: Benchmarking Full-Body Musculoskeletal Motor Control Across Tasks, Learning Paradigms, and Physiological Metrics. Mengtao Ou, Zongzheng Zhang, Zhenghao Xiao, Yixuan Pan, Ziwen Zhuang, Hang Zhao, Hongyang Li, Yanan Sui, Libin Liu, Hao Zhao

Organization

Workshop Organizers

Pieter Abbeel

Professor at UC Berkeley

Carlo Sferrazza

Incoming Assistant professor at UT Austin, Research Scientist at Amazon

Youngwoon Lee

Assistant Professor at Yonsei Unviersity

Toru Lin

PhD at UC Berkeley

Ziwen Zhuang

PhD at Tsinghua

Bike Zhang

Postdoc at UC Berkeley

Calls

Call for papers

We welcome submissions of full papers as well as work-in-progress and accept submissions of work recently published or currently under review.

In general, we encourage two types of papers:

Empirical paper: Submissions should focus on presenting original research, case studies or novel implementations in the fields related to the workshop (see potential topics below).
Position paper: Authors are encouraged to submit papers that discuss critical and thought-provoking topics within the scientific community.

Potential topics include:

Reinforcement learning for whole-body control and bimanual manipulation
Teleoperation systems for humanoid robots (or other complex robotic systems) and imitation learning
Learning models (e.g. dynamics, perception) and planning for complex, mobile robotic systems
Benchmark and task proposals for whole-body control and manipulation
Multimodal, whole-body sensing and perception
Simulation to real world transfer
Learning from human videos

Important Dates

Submission deadline: June 8 15, 2026
Notification of acceptance: June 18 22, 2026
Camera-ready papers due: June 30, 2026
All deadlines are AoE time.

Submission Guidelines

Submission link: OpenReview

Accepted papers will be presented as posters, and a subset of them will be selected for oral presentation.

There is no page limit but recommended 4-8 pages (excluding references and appendix). Submissions must follow the RSS template and style, and should be properly anonymized.

Dual Submission Policy

We welcome papers that have never been submitted, are currently under review, or recently published. Accepted papers will be published on the workshop homepage, but will not be part of the official proceedings and are to be considered non-archival.