It feels hard to do robotics research these days. There seems to be this pressure to deliver "large scale" results to keep up with vision/language, to tie your results to the LLM bandwagon and ride the wave
LLMs have generally sucked the oxygen out of the room, but robotics seems to have been particularly impacted
Been meeting with robotics experts over the last few days, and the mood is gloomy to say the least
What makes a well-written grant proposal? After two decades of writing, revising, and reviewing grant proposals, I recently discovered the blog posts of @amderrington, who like no one else captures the most crucial points. A selection.👇
Biggest mental shift while switching from classic to scientific programming: explicit “for” loops are now extremely expensive.
Instead, you express as much as you can by chaining hyperoptimized lower-level “for” loop primitives, eg matrix multiplies.
Fun & new way of thinking.
Last month at the Stanford ISL colloquium I discussed the early history of machine learning, noting the astounding groundwork done before 1970.
youtube.com/watch?v=47tKry…
@heidiann360 For an illustration of how pointless it is to spend too much time drawing diagrams, I recommend looking at Figure 1 here arxiv.org/abs/quant-ph/0…
"Synergy of Prediction and Control in Model-based Reinforcement Learning"
My thesis is now available, thank you @Berkeley_EECS and all who contributed to this. It has been a massive journey.
www2.eecs.berkeley.edu/Pubs/TechRpts/…
I'll explain what I wrote about and a few reflections 👇
1/
Dove into a new area at the beginning of the year: dexterous hand manipulation. It's been incredibly gratifying to learn new things on the daily: new simulator (MuJoCo), inverse kinematics (differential & QP), and now motion capture and retargeting (little bit of Blender) 😀
Favorite quote so far from Emo Todorov's CoRL 2018 tutorial: "The world is not really stochastic. If you've noticed -- a robot doesn't just spontaneously start shaking. Unless you hook up an RL algorithm to it."
I’ve been working with MuJoCo + dm_control full-time for the last 2 months, and it’s been an absolute pleasure. Completely sold! So much respect for @DeepMind’s clarity of thought and foresight re:the API design. Will write up a blog post at a more appropriate time!
Russ Tedrake. Underactuated Robotics: Algorithms for Walking, Running, Swimming, Flying, and Manipulation (Course Notes for MIT 6.832).
underactuated.mit.edu
We introduce a new method to learn simulators from depth and RGB videos. The "URDF" of an articulated rigid-body mechanism is reconstructed, and the parameters of the simulator inferred through Bayesian inference.
Website: eric-heiden.github.io/video2sim/
Paper: arxiv.org/abs/2203.10488
A lot of people complain that RL doesn't work and RL researchers are still playing games. While this criticism is true to some extent, there's been a new trend of applying RL for real-life problems. This is a thread of notable papers split by the topic.
1/n
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627 Followers 50 Following65th IEEE Conference on Decision and ControlDec. 15-18 2026, Honolulu, Hawaii, USA. General Chair: Jorge Cortes. Program Chair: Lacra Pavel
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