Cover Image for Robotics & World Models Reading Club 29: Data, Hardware & the Scaling Problem in Robotics. SF 9/19

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🤖 Saturday Reading Club on Robotics & World Models for AI Researchers in SF
Hosts: Junfan Zhu, Aurora Feng
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Robotics & World Models Reading Club 29: Data, Hardware & the Scaling Problem in Robotics. SF 9/19

Name: Robotics & World Models Reading Club 29: Data, Hardware & the Scaling Problem in Robotics. SF 9/19
Start: 2026-09-19T14:00:00.000-07:00
End: 2026-09-19T17:00:00.000-07:00
Location: San Francisco, CA

Saturday Robotics

San Francisco, CA

Past Event

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About Event

Robotics & World Models Reading Club 29: Data, Hardware & the Scaling Problem in Robotics. SF 9/19

A high-signal reading group for AI researchers & builders pushing the frontiers of robotic world models, WAMs, and embodied intelligence. In our previous sessions, we brought together researchers and engineers from Boston Dynamics, Dyna, Google DeepMind, NVIDIA, Stanford, UC Berkeley, Physical Intelligence, Tesla, Generalist, Rhoda AI, and leading Bay Area robotics startups.

Hosted by Junfan Zhu & Aurora Feng.

Support Saturday Robotics Inc: https://donate.stripe.com/28EcN52rjgeY1fJboYgEg00

Reading Club 29's Core Theme — Data, Hardware & the Scaling Problem in Robotics

The Best Glove Is Rigid: Why Robot Hands Should Be Built Around Their Data
Joe Dong — Founder & CTO, Chestnut Robotics
Can Classical Robotics Still Scale? Lessons from a Robot That Bought Coffee
Tony Pratkanis — ex-Stanford, Google

Keynote 1: The Best Glove Is Rigid: A Preview of a Hand Built Around Its Data

Joe Dong, Founder & CTO of Chestnut Robotics

He builds dexterous hands together with the data systems that train them. He previously worked on autonomous driving at Waymo and Xpeng Motors. He writes Physical AI Deep Dives at newsletter.joedong.ai. His recent essays argue that data sourcing, not degrees of freedom, decides what a robot hand should be.

Egocentric human video is becoming the substrate for robot foundation models, but fine manipulation is won or lost at the instant of contact, and that instant is the one thing video cannot measure: the contact hides behind the finger, and force never reaches the pixels. This talk argues that the data glove filling that gap should be rigid, and previews the hand and capture system we built on that premise. (1) Hardware. I will argue against the field's default. Soft is the root of every glove problem: calibration that drifts each time you put it on, no fixed geometry for locating contact, tactile sensors mounted on deforming fabric. Rigid functional surfaces on anatomically aligned joints turn contact localization into forward kinematics and give touch a stable mount, at the cost of a dexterity tax I will argue is worth paying. (2) Co-design. Every retargeting pass from a human hand to a robot hand leaks contact precision, so the glove's geometry should be the robot's geometry. The right dexterous hand is the one a human can capture, not the most dexterous one. I will show the co-designed pair, Aero UMI and Aero Hand, and what fell out of reversing the usual order of hand and capture device. (3) From capture to policy. I will cover the engineering that makes human demonstration and robot execution correspond: ergonomic fit as a data-quality problem, three distinct meanings of accuracy and the active vision-based calibration that ties them together, temporal alignment, and geometry-aware inpainting. Then how we validate the resulting data with Diffusion Policy, and where a small model for fine manipulation sits beneath a long-horizon planner.

Keynote 2

Tony Pratkanis (Ex Stanford + Google, Currently Stealth Startup)

In the now-distant year of 2012, my collaborators and I completed, via robotic means, a fully autonomous procurement of a cup of coffee. For this purpose, we utilized a PR2 - a full-sized wheeled humanoid robot of the era. The robot departed from our laboratory, proceeding through numerous doors and an elevator, until it did arrive upon a traditional coffee shop. Therewithin, the robot legally purchased a coffee, navigated a return through those same doors and elevator, and subsequently delivered the beverage to our academic advisor.

This discourse shall present an overview of the methodology of the aforementioned, and the implications it holds for the scalability of classical robotics algorithms such as SLAM, classical planners, and hand-crafted scripts. Furthermore, I shall also present my subsequent research concerning the interleaving of digital robot application stores with task-level classical planning algorithms, thereby scaling robotics by crowd-sourcing hand-crafted robot programs globally. In conclusion, we shall examine contemporary instances of these algorithms as they are presently deployed within the active commercial robots of the current day, and the challenges which these methods have yet to overcome.

Pre-Readings

newsletter.joedong.ai. Data Gloves Should Be Rigid
https://sr.stanford.edu/?page_id=793.

Location

San Francisco

Date & Time

Saturday, September 19, 2026 | 2:00 PM – 5:00 PM

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Agenda

2:00 PM – 2:30 PM Door Opens & Social

Food 😋, beverages🧋 and UNLIMITED strawberries 🍓 (our official reading club fruits ☺️😄).

2:30 PM – 4:00 PM Keynotes by Joe Dong and Tony Pratkanis

YouTube Recording: TBD (We are looking for recording volunteers)

4:00 PM – 5:00 PM Q&A, open-floor roundtable (10–20 min per topic) on spotlight papers or any paper you’d like to highlight. Feel free to share why the paper matters and its technical details.

Future events

#iros-reading-club-31-0928: 🍾 IROS 2026 x Saturday Robotics — Robotics Research Night | Reading Club 31. Pittsburgh 9/28

Session 31 Luma: https://luma.com/tzbw7n61

Past events

#reading-club-28-0912: Booster T2: The Next Frontier of Open Humanoid Robotics

Session 28 Luma: https://luma.com/00z3oxw6

#reading-club-27-0905: Rethinking Robot Development: Co-Designing Morphology, Sensing, and Learning

Chenyang Ma (Applied Intuition, UNC)

Session 27 Luma: https://luma.com/jm9jceqr

#reading-club-26-0829: Sunnyvale 8/29

Session 26 Luma: https://luma.com/enowqo5v

#reading-club-25-0822: Contact-Rich Robot Learning from Human Videos and Tactile. SF 8/22

Kelin Yu (Maryland, Amazon FAR)

Session 25 Luma: https://luma.com/yl76re1b

#reading-club-24-0820: Saturday Robotics x EAI @ WRC Beijing | PHYSICAL AI UNPLUGGED —— 与 Physical AI 研究者的一场非正式夜谈

• 李晓帆 — Head of World Models, X Square Robot (自变量机器人)

• Tongzhou Mu — Research Scientist, Rhoda AI

• Haoyi Niu — University of California, Berkeley

• Yufei Wang — Member of Technical Staff, Genesis AI

• Shibo Zhao — Research Scientist, Amazon FAR

• 郑思鹏 — Technical Partner, Being Beyond

• Tianle Zhang — Embodied AI Researcher, JD Explore Academy

• Yihang Li — Embodied AI Researcher, JD Explore Academy

Session 24 Luma: https://luma.com/jezexfza

#reading-club-23-0815: Engineering Robotic Simulators for Evaluation and Beyond. SF 8/15

Kaifeng Zhang (Columbia, World Labs)

Session 23 Luma: https://luma.com/non72bev

#reading-club-22-0808: ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow. SF 8/8

Haoyi Niu (UC Berkeley)

Session 22 Luma: https://luma.com/7nnl4a5r
Reading Club 22 Review: https://x.com/junfanzhu98/status/2086482247344079100?s=20
Reading Club 22 Recap: https://x.com/junfanzhu98/status/2086484540013560280?s=20

#reading-club-21-0801: Vision-Language-Kinematics Supervision for Perception-Based Humanoid Loco-Manipulation — SF 8/1

Yen-Jen Wang (UC Berkeley, Amazon FAR)

Session 21 Luma: https://luma.com/4xkibxbh
Reading Club 21 Review: https://x.com/junfanzhu98/status/2083948325112533456?s=20
Reading Club 21 Recap: https://x.com/junfanzhu98/status/2083950393734975839?s=20

#reading-club-20-0725: Agentic Robotics Models (ENPIRE and Cap-X), Mountain View 07/25

Haoru Xue (UC Berkeley)

Kris Hauser (Samsung Research America, Robot Intelligence Lab)

Session 20 Luma: https://luma.com/5ltk12w5
Reading Club 20 Review: https://x.com/junfanzhu98/status/2081420671180284190?s=20
Reading Club 20 Recap: https://x.com/junfanzhu98/status/2081423890988044794?s=20

#SIGGRAPH-reading-club-19-0722: SIGGRAPH x Saturday Robotics — World Models for Robotics: Bridging Graphics, Simulation & Physical Intelligence | Reading Club 19, LA 07/22

Session 19 Luma: https://luma.com/yh2212ac
Reading Club 19 Review: https://x.com/junfanzhu98/status/2081923681627079055?s=20
Reading Club 19 Recap: https://x.com/junfanzhu98/status/2081924824709124174?s=20

#reading-club-18-0718: Causal World Models For Real-World Intelligence. SF 07/18

Guanming Wang & Bill (General Instinct, YC P26)

Feng Fan (UCSD, Aether AI)

Session 18 Luma: https://luma.com/f74eguvr
Reading Club 18 Review: https://x.com/junfanzhu98/status/2078738476602884502?s=20
Reading Club 18 Recap: https://x.com/junfanzhu98/status/2078747463058694625?s=20
Autonomous Panel Moderation: Rebuilding the Factory: Physical AI on the Production Line: https://x.com/junfanzhu98/status/2078385948887490814?s=20

#reading-club-17-0711: Soft Tactile-Centric Multimodal Intelligence Toward Safe and Dexterous Manipulation. SF 07/11

Quan Luu, Purdue.

Session 17 Luma: https://luma.com/e53zawq2
Reading Club 17 Review: https://x.com/junfanzhu98/status/2076205508646850819?s=20
Reading Club 17 Recap: https://x.com/junfanzhu98/status/2076207394426917187?s=20

#private-lunch-icml-0709: Saturday Robotics x ICML Private Lunch (Seoul)

Private Lunch: https://luma.com/khqg11gt

#reading-club-16-0704: The Embodied AI Hardware Stack — Supply Chain, Sensors, and the Data Flywheel — SF 07/04

Jerry Huang, Robotics Center of Silicon Valley.

Session 16 Luma: https://luma.com/cgzyfpeb
Reading Club 16 Review: https://x.com/junfanzhu98/status/2073666442512547957?s=20
Reading Club 16 Recap: https://x.com/junfanzhu98/status/2073667174678589620?s=20

#reading-club-15-0627: Scaling Touch: Flexible Tactile Skin for Dexterous Manipulation

Binghao Huang, Columbia, Amazon FAR.

Session 15 Luma: https://luma.com/7lts5ppf
Reading Club 15 Review: https://x.com/junfanzhu98/status/2071129728984273105?s=20
Reading Club 15 Recap: https://x.com/junfanzhu98/status/2071132114226139489?s=20

#deep-tech-week-14-0625: Deep Tech Week Research Night

SPEAR: A Simulator for Photorealistic Embodied AI Research. (ECCV 2026 accepted) by Mike Roberts, Senior Research Scientist, Adobe Research.

Bogdan Cristei, Venture Partner at SHACK15 Ventures.

Simone Totaro, CTO at Saturn Dynamics.

Shumo Chu, CEO at General Intelligence Labs.

Margaret Zhang, CEO at ThirdBrain Labs.

Session 14 Luma: https://luma.com/l1g9c2l1
Deep Tech Week 14 Review: https://x.com/junfanzhu98/status/2070417784560066592?s=20
Deep Tech Week 14 Recap: https://x.com/junfanzhu98/status/2070420270964514923?s=20

#reading-club-13-0620: HumanEgo: Train Robot Policy from 30 min Egocentric Videos — SF 0620

Session 13 Luma: https://luma.com/6vkhxnum
Reading Club 13 Review 1: HumanEgo: Zero-Shot Robot Learning, Human Egocentric Video, Leo Wang, Amazon FAR & UMaryland https://x.com/junfanzhu98/status/2068603103138713824?s=20
Reading Club 13 Recap 1: https://x.com/junfanzhu98/status/2068605511549743127?s=20
Reading Club 13 Review 2: Causal World Models: Biwei Huang, Aether AI & UCSD
https://x.com/junfanzhu98/status/2068743219685560453?s=20
Reading Club 13 Recap 2: https://x.com/junfanzhu98/status/2068746229643936177?s=20

#reading-club-12-0613: Origami Robotics (YC W26) on Dexterity

Session 12 Luma: https://luma.com/5w7c1t2a
Reading Club 12 Review: https://x.com/junfanzhu98/status/2066275974988337178?s=20
Reading Club 12 Recap: https://x.com/junfanzhu98/status/2066278639554245097?s=20

#cvpr-denver-11-0606: 🤖🥘 Saturday Robotics x Manycore Tech x Neural Motion | CVPR 2026 Denver Research Night | Robotics & World Models Reading Club 11

Junfan Zhu & Aurora Feng, Founders of Saturday Robotics

Anthony Zhao, Head of North America at Manycore Tech SpacialVerse

Aurora Feng, Founder at Neural Motion. NM-GenET.

Max Zhaoshuo Li, Robotics and World Model Tech Lead at NVIDIA Cosmos. Cosmos 3.

Xiaofan Li, World Model Tech Lead at X Square Robot. WALL-WM.

Zesen Zhao, University of Michigan. Test-Time Scaling for World Action Models via Zero-Shot Geometric Verification.

Pengyi Liao. VGGT-Ω: From 3D Reconstruction to Scalable Spatial Representation.

Jie Wang, University of Pennsylvania, GRASP Lab. Toward a Robotics MMLU: Lessons from Sim & Real Evaluations of Generalist Policies.

Gordon Qian, Senior AI Researcher at Snap. Diffusion-DRF: Free, Rich, and Differentiable Reward for Video Diffusion Fine-Tuning.

YouTube livestream: Watch on YouTube
CVPR Denver Research Night Luma: https://luma.com/zamm9g2g
CVPR Denver Research Night Lightning Talks Review: https://x.com/junfanzhu98/status/2065102150418788581?s=20
CVPR Denver Research Night Lightning Talks Recap: https://x.com/junfanzhu98/status/2065104616497524843?s=20
CVPR Hot Takes Review: https://x.com/junfanzhu98/status/2065234892653547904?s=20
CVPR Hot Takes Recap: https://x.com/junfanzhu98/status/2065236892988416166?s=20

#reading-club-10-0530: Bringing Robots to Life — Learning Humanoid Instincts from the Body Up | San Francisco 0530

Haochen Shi (Stanford, co-advised by Karen Liu & Shuran Song)

Session 10 Luma: https://luma.com/czz76qe1
Reading Club 10 Recap: https://x.com/junfanzhu98/status/2061145697693683878?s=20

#private-dinner-01-0529: Robo Plov x Saturday Robotics

Private Dinner 01 Luma: https://luma.com/3rzqwond
Private Dinner 01 Review: https://www.linkedin.com/posts/junfan-zhu_saturday-robotics-was-excited-to-host-its-activity-7466384182190182400-Zgnv?utm_source=share&utm_medium=member_desktop&rcm=ACoAABxP-p0BpUNGDf347aKh_1uJAPzG4er0As8

#reading-club-09-0523: CVPR Warm-up & Founders Spotlight — DeltaWorld + VisuoTactile Dexterous Hands

Tommie Kerssies (Amazon Frontier AI & Robotics)

Arjun Subramaniam (Factory Intelligence)

Session 09 Luma: https://luma.com/wooiz0bf
Reading Club 09 Review: Part 1: Robotics & World Model Reading Club 9.1: CVPR Warm-up— A Frame is Worth 1 Token: DeltaToken. https://x.com/junfanzhu98/status/2058449627184267621?s=20
Reading Club 09 Review: Part 2: Robotics & World Model Reading Club 9.2: Tactile Sensor & Reliable Manipulation in Production. https://x.com/junfanzhu98/status/2058461947637694948?s=20

#reading-club-08-0516: Embodied Human Data as the “Internet of Motion and Behavior”

Ryan Punamiya (NVIDIA Gear, Georgia Tech)