Robotics & World Models Reading Club 17: Soft Tactile-Centric Multimodal Intelligence Toward Safe and Dexterous Manipulation. SF 07/11

Robotics & World Models Reading Club 17: Soft Tactile-Centric Multimodal Intelligence Toward Safe and Dexterous Manipulation — San Francisco 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, Google DeepMind, NVIDIA, Stanford, UC Berkeley, Dyna, Physical Intelligence, Tesla, Generalist, Rhoda AI, and leading Bay Area robotics startups. Hosted by Junfan Zhu & Aurora Feng. Supported by Neural Motion, a universal cross-embodiment data representation layer for embodied AI. Reading Club 17's Core Theme Soft Tactile-Centric Multimodal Intelligence Toward Safe and Dexterous Manipulation Quan Luu, Postdoc at Purdue University, and incoming Assistant Professor at the University of Nebraska-Lincoln (https://quan-luu.github.io/) As robots transition from structured industrial settings to unstructured environments, they are required to interact with humans and objects in a safe and effective manner. However, achieving robust and safe operation remains a major challenge due to the limited understanding of physical contact. In this seminar, I present my research on advancing embodied robot intelligence through tactile-centric multimodal sensing, perception, and learning. I first introduce the design of soft sensorized robotic components that integrate tactile feedback with proximity and visual sensing to capture rich physical interaction signals. I then demonstrate how these capabilities are integrated into learning and control frameworks to enable reactive manipulation and contact-rich behaviors. Together, this work illustrates how the integration of soft sensorized robot bodies with multimodal perception and control enables safe and adaptive robot behavior while improving overall contact-rich manipulation performance. Pre-Readings ManiFeel preprint and project website: Pre-print: https://arxiv.org/pdf/2505.18472 Website: https://zhengtongxu.github.io/manifeel-website/ Vision-Based Proximity and Tactile Sensing for Robot Arms: Design, Perception, and Control. IEEE TRANSACTIONS ON ROBOTICS, VOL. 41, 2025 Simulation, Learning, and Application of Vision-Based Tactile Sensing at Large Scale. IEEE TRANSACTIONS ON ROBOTICS, VOL. 39, NO. 3, JUNE 2023 Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies. arXiv:2604.27224v2 (IROS 2026) CONTACT: CONtact-aware TACTile Learning for Robotic Disassembly. arXiv:2603.08560v1 (IROS 2026) Location San Francisco (Downtown) Date & Time Saturday, July 11, 2026 | 2:00 PM – 5:00 PM Join Discord Community https://discord.gg/WH7DrTHRXK Follow Saturday Robotics on X https://x.com/saturdayrobotic 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 Keynote by Quan Luu, Postdoctoral Researcher Purdue University (https://quan-luu.github.io/) Online access via Zoom: TBD 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 Past events #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 T