Robotic Systems Lab

@leggedrobotics

The Robotic Systems Lab designs machines, creates actuation principles, and builds up control technologies for autonomous operation in challenging environments.

Zurich, Switzerland rsl.ethz.ch Joined March 2016

172 Following 39K Followers 722 Posts

Latest posts 5

Robotic Systems Lab @leggedrobotics 6d

Our new work WayTrace: an off-the-shelf VLM, an onboard trace model, and an RL policy take a robot from web-map directions to 2.35 km of real-world missions in Zurich.

Details in the thread 👇

Manthan Patel ✈️ CoRL @patelm99 6d

We gave a robot the walking directions you'd get from a web map.

Then we let it find its own way through Zurich: crosswalks, stairs, crowded streets, construction sites, 2.35 km in total.

Introducing WayTrace 🧵👇

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Robotic Systems Lab @leggedrobotics Nov 3

In our latest work @corl_conf, we present ADAPT: an end-to-end framework for interactive, text-conditioned humanoid control, in contrast to dominant pipelines that generate kinematic motions for a separate RL tracker. 🤖

🌐 wuyan01.github.io/ADAPT-project/

Full video in🧵

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Chenhao Li 📌 CoRL @breadli428 Nov 3

Dominant text-to-motion pipelines generate kinematic motions for a separate tracker.

Instead, in our @corl_conf work ADAPT, we solve humanoid language control end-to-end closed-loop, where the robot must continuously respond to changing commands.

🌐Page: wuyan01.github.io/ADAPT-project/

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Robotic Systems Lab @leggedrobotics Oct 29

We hope to change ideas on how perception should integrated in rough terrain locomotion with our latest work

Watch Your Step: Anticipated Perception for Humanoid Locomotion

We predict and perceive only where it matters.

🌐 leggedrobotics.github.io/watch-your-step
📷 arxiv.org/abs/2610.29612

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Chenhao Li 📌 CoRL @breadli428 Oct 29

We only care about where our feet are about to land when we walk. Why shouldn’t humanoids?

Introducing Anticipated Perception for Humanoid Locomotion, anticipating upcoming footholds and perceiving only the terrain patches that matter for next step.👣

🌐 leggedrobotics.github.io/watch-your-step

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Robotic Systems Lab @leggedrobotics Oct 29

We walk without worrying about what’s behind us. Why should humanoids?

We introduce Anticipated Perception for Humanoid Locomotion: a new approach that focuses terrain perception on where the feet are about to land. 👣

🌐 leggedrobotics.github.io/watch-your-step 📷 arxiv.org/abs/2610.29612

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Robotic Systems Lab @leggedrobotics Oct 28

Introducing DeFM: a foundation model for depth images, built for robotics.

Weights, code and a browser demo are out!

Manthan Patel ✈️ CoRL @patelm99 Oct 28

Vision foundation models like DINO and SigLip now power much of robot learning.

But they are built for RGB. What about depth?

Introducing DeFM: a foundation model for depth images, built for robotics.

🌐 de-fm.github.io

Weights, code, and demo are out today 🧵

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