Learning Legged Locomotion Workshop @ ICRA 2019

We're pleased to announce that our workshop has been accepted as a full day workshop at ICRA 2019! Details to follow.


Legged robots are notoriously difficult to control. Recent progress in machine learning has shown promises to design robust and agile locomotion controllers automatically. However, most of these learning-based methods are limited to simulation or to simple hardware platforms. Many challenges remain in bringing these learning-based control approaches to real legged robots, including the reality gap, safe exploration, continuous data collection, data-efficient learning algorithms, experimental evaluation, and hardware robustness.

This workshop brings together experts in the fields of legged robotics and machine learning/reinforcement learning to discuss the state-of-the-art and challenges in learning-based control of legged robots.

Topics of Interest

Learning based control for legged locomotion:

  • Reinforcement learning / evolutionary strategies
  • Model based learning
  • Learning in simulation
  • On-robot learning
  • Perception for unstructured terrain locomotion
  • Sim-to-real transfer
  • Hardware platforms for learning
  • Benchmarks
  • State estimation
  • ...

Robot Demos

Showcase the capabilities of your legged robot! Email us to contribute with your demo.

We are coordinating with the Towards Real-World Deployment of Legged Robots workshop to provide logistics support for live demos at our workshop.

More info coming soon!

Organizing Committee

contact: learningleggedlocomotion@gmail.com






Schedule (preliminary)

09:00 - 09:10 Introduction

09:10 - 10:40 Session 1 (3 speakers)

10:40 - 11:10 Coffee break / Robot demos

11:10 - 12:40 Session 2 (3 speakers)

12:40 - 14:00 Lunch break

14:10 - 15:40 Session 3 (3 speakers)

15:40 - 16:20 Coffee break / Robot demos

16:20 - 17:00 Panel discussion

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Invited Speakers

Aaron Ames (Caltech)

Akshara Rai (CMU)

Erwin Coumans (Google)

Michiel Van de Panne (UBC)

Jemin Hwangbo (ETH Zurich)

Sangbae Kim (MIT)

Stuart Anderson (NVIDIA)

More speakers to be announced soon!