Russ Tedrake

@RussTedrake

Co-Founder and CEO at Walden Robotics. Professor at MIT.

locomotion.csail.mit.edu/russt.html

Joined July 2022

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Russ Tedrake
@RussTedrake
Aug 26
Thanks for hosting me, Brad.
Brad Porter
@BradPorter_
Aug 25
The best case for wheels I've heard came from the guy who has taught legged locomotion at MIT for 20 years. AMR safety cases assume you slow proportional to distance and come to rest. A balancing biped may need to take steps to stop. The safety zone explodes and the robot ends
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Russ Tedrake
@RussTedrake
Aug 21
When we first started working on Diffusion Policy, which felt like an "unlock" for fitting human demonstration data, the explanation I gave myself was that "human demonstration data was subtly much more multimodal than we thought, so we need the modeling power of denoising
Michael Zeng
@michzeng_
Aug 20
Action chunking — especially executing long action sequences open-loop — is widely used in imitation learning for robotic manipulation. Why is it so effective and do we really need it? We find a key reason: Long open-loop execution helps short-context policies imitate
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Russ Tedrake
@RussTedrake
Jul 15
Thanks to @HeySamantha and @Bloomberg for covering our launch
Toyota-Backed Startup Walden Robotics Comes Out of Stealth With $1.1 Billion Valuation
From bloomberg.com
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Russ Tedrake
@RussTedrake
Jul 15
In January, I started "building something new" with an incredible team. Today I finally get to share some first details about what we've been building. We've called it Walden Robotics (waldenrobotics.com). I thought long and hard about my own reasons for starting this
Walden Robotics | Build the Future of Physical AI with Us
From waldenrobotics.com
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Russ Tedrake
@RussTedrake
Jun 20
When it comes to diffusion policies, VLAs, and LBMs, we all know that data quality matters. Many of us have spent considerable time filtering data, and discarding large amounts of data that might not be considered to be sufficiently high quality. This feels very inefficient.
Adam Wei
@adamwei_
Jun 18
🤖 We introduce Ambient Diffusion Policy, a simple and principled method for training policies with suboptimal data in robotics. Suboptimal data is everywhere in robotics… ❌ Data filtering is wasteful ❌ Co-training learns both good and bad features ✅ Ambient Diffusion Policy
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