Embedded Files
The BeNeRL Seminar Series are monthly online talks by RL researchers from all over the world. The intention is to primarily give a platform to advanced PhD students and early career researchers to 1) display their work and 2) share their practical RL experience (i.e., how do you manage large-scale RL experiments as a new researcher in the field, a topic that is often skipped in talks). We maintain a summary of the main advice on experimentation.
The seminar is online and takes place on every second Thursday of the month, 16.00-17.00 (CET)
(unless there is a conflict with an important machine learning conference, when we try to shift by one week)
Date: Oct. 8, 16.00-17.00 (Amsterdam Time Zone)
Title: Robots that See and Act with Their Whole Body
Link: Zoom Link - Click Here
Abstract: For decades, robot manipulation has largely centered on arms with six or seven degrees of freedom, an end-effector for interacting with objects, and one or two cameras. What becomes possible when we expand these design choices? More joints offer greater flexibility, distributed sensors provide richer perception, soft and growing bodies enable access to confined spaces, and mobility extends the robot's workspace. Yet these capabilities also introduce challenges that have traditionally constrained robot design: complex control, unpredictable dynamics, and increasingly large observation and action spaces. This talk explores how robot learning allows us to embrace this complexity and enable new capabilities. It introduces RoboPanoptes, a robot that achieves whole-body dexterity through whole-body vision; PanoVine, a system for controlling a soft, growing vine robot through whole-body visual feedback; and HoMMI, which learns whole-body mobile manipulation and active perception directly from robot-free human demonstrations. These systems show how pairing novel hardware capabilities with appropriate learning methods and interfaces enables intuitive teaching, robust control, and scalable data collection for robots that see and act with their whole bodies.
Schedule
Schedule
Talks are always online and take place between 16.00-17.00 (Amsterdam Time Zone).
2023
Thu Oct 12: Benjamin Eysenbach (Princeton) Connections between Reinforcement Learning and Representation Learning
Thu Nov 16: Cansu Sancaktar (Max Planck Institute) Playful Exploration in Reinforcement Learning
2024
Thu Feb 8: Pierluca D'Oro (Mila) On building World Models better than reality
Thu April 11: Minqi Jiang (Google Deepmind) Learning Curricula in Open-Ended Worlds
Thu May 16: Edward Hu (University of Pennsylvania) The Sensory Needs of Robot Learners
Thu June 13: Nicklas Hansen (UC San Diego) Data-Driven World Models for Robots
Thu Sep 12: Daniel Palenicek (TU Darmstadt) Sample Efficiency in Deep RL: Quo Vadis? (slides)
Thu Oct 10: Ademi Adeniji (UC Berkeley) Reinforcement Learning Behavioral Generalists - Top-Down and Bottom-Up (slides)
Thu Nov 14: Tal Daniel (Technion) Particles to Policies: Object-Centric Learning in Pixel-Based Decision Making (slides)
Thu Dec 19: Hojoon Lee (KAIST AI) Designing Neural Network Architecture for Deep Reinforcement Learning (slides)
2025
Thu Mar 13: Andrea Tirinzoni (Meta FAIR) Pre-training Behavioral Foundation Models via Zero-shot Reinforcement Learning
Thu May 8: Qiyang Li (UC Berkeley) Leveraging unlabeled task-agnostic offline data for efficient online exploration
Thu June 12: Anikait Singh (Stanford University) Towards Scalable RL Machinery for LLM Post-Training
Thu Dec 11: Theresa Eimer (Leibniz University of Hannover) "Is My RL Algorithm a Good Tool?" - What Evaluation Strategies Tell Us About Our Algorithms
2026
Thu Jan 8: Andrew Wagenmaker (UC Berkeley) What Does RL Theory Have to Do with Robotics?
Thu Feb 12: Claas A. Voelcker (UT Austin) On-policy value learning at 10000 frames per second (slide)
Thu Mar 12: Elle Miller (University of Edinburgh) Is RL enough? Achieving blind superhuman dexterity with the help of World Models (slides) (record) (blogpost)
Thu July 9: Michal Nauman (University of Warsaw) Scaling in value-based RL
Thu Oct 8: Xiaomeng Xu (Stanford University) Robots that See and Act with Their Whole Body
If you have any questions about the seminar series, feel free to contact:
Zhao Yang: z.yang(at)liacs.leidenuniv.nl
Page updated
Google Sites
Report abuse