Waterloo Robot Learning Reading Group - Sim2Real / Whole-Body Control (Week 3)
Meetup to discuss state-of-the-art research on robot learning (humanoids, foundation models, RL, sim2real, etc.), similar to the Toronto ML/Systems Reading Group and Vector Institute's Machine Learning Lunches- list of topics & articles below - all are welcome! 🎉
Pizza sponsored by Palatial!
Previous week: https://luma.com/ympgqji6
Topic - Sim2Real / Whole-body Control
6:00pm - Kalaria, et al., 2025. DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion by Ayush Garg
AlphaXiv annotation link (post your questions / comments there before reading group!)
Additional Reading List:
Xie, et al., 2023. OmniControl: Control Any Joint at Any Time for Human Motion Generation.
Cheng, et al. 2024. Expressive Whole-Body Control for Humanoid Robots.
Fu, et al., 2024. HumanPlus: Humanoid Shadowing and Imitation from Humans.
He, et al., 2024. HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots.
Dugar, et al., 2024. Learning Multi-Modal Whole-Body Control for Real-World Humanoid Robots.
Ji, et al., 2024. ExBody2: Advanced Expressive Humanoid Whole-Body Control.
Kim, et al., 2024. ARMOR: Egocentric Perception for Humanoid Robot Motion Planning in Dense Environments.
Serifi, et al., 2024. VMP: Versatile Motion Priors for Robustly Tracking Motion on Physical Characters.
He, et al., 2024. Learning Human-to-Humanoid Real-Time Whole-Body Teleoperation (H2O).
He, et al., 2024. OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning.
van Marum, et al., 2024. Revisiting Reward Design and Evaluation for Robust Standing and Walking.
Radosavovic, et al., 2024. Humanoid Locomotion as Next Token Prediction.
Gu, et al., 2024. Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning (ETH-Loco).
Zhang, et al., 2025. FALCON: Learning Force-Adaptive Humanoid Loco-Manipulation.
Li, et al., 2025. CLONE: Closed-Loop Whole-Body Humanoid Teleoperation for Long-Horizon Tasks.
Ze, et al., 2025. TWIST: Teleoperated Whole-Body Imitation System.
Zhang, et al., 2025. Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space (R2S2).
Chen, et al., 2025. GMT: General Motion Tracking for Humanoid Whole-Body Control.
Allshire, et al., 2025. Visual Imitation Enables Contextual Humanoid Control.
Zhang, et al., 2025. Track Any Motions under Any Disturbances.
He, et al., 2025. Attention-Based Map Encoding for Learning Generalized Legged Locomotion.
Background knowledge:
Schulman, et al., 2017. Proximal Policy Optimization Algorithms.
Chi, et al., 2023. Diffusion Policy: Visuomotor Policy Learning via Action Diffusion.
Extra articles:
https://www.agilityrobotics.com/content/training-a-whole-body-control-foundation-model?curius=4304
https://gofai2robots.substack.com/p/the-emerging-humanoid-motor-cortex
Questions we should answer as we read these papers:
What are the authors trying to do? Articulate their objectives.
How was it done prior to their work, and what were the limits of current practice?
What is new in their approach, and why do they think it will be successful?
What are the mid-term and final “exams” to check for success? (i.e., How is the method evaluated?)
What are limitations that the author mentions (any that they omit)?