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Excited to share what I've been working over the last few months! We taught Spot to lift, roll, and stack tires completely autonomously. It uses its arms, body, and legs to manipulate heavy objects at speed.
We also show RL-based tire uprighting, where the tire literally flies into the air. This illustrates just how dynamic whole-body manipulation can be.
If you're interested in working on whole-body manipulation at @rai_inst feel free to use this link jobs.lever.co/rai?lever-via=…
Check out the blog post for more details: rai-inst.com/resources/blog/…
I am really happy to finally share this work! Huge congrats to @albert_h_li and @pdculbert for the effort they put in making the tool hackable and interactive.
Try it!🐍
pip install judo-rai
Simon LC retweeted
Our new paper shows how task representations learned via temporal alignment enable compositional generalization for conditional policies. This allows robots to solve compound tasks by implicitly decomposing them into subtasks.
Simon LC retweeted
Learning bimanual, contact-rich robot manipulation policies that generalize over diverse objects has long been a challenge.
Excited to share our work: Planning-Guided Diffusion Policy Learning for Generalizable Contact-Rich Bimanual Manipulation!
glide-manip.github.io
🧵1/n
Simon LC retweeted
ICYMI: For #CoRL2024 we released a dataset of 3.5M (!) dexterous grasps, with multi-trial labels and perceptual data for 4.3k objects.
Our takeaways: scale matters, and refining grasps > better sampling. Hoping our data can enable more vision-based grasps in hardware!
There have been many recent big grasping datasets, but few demos of real-world grasping using generative models. How do we achieve this?
Introducing: Get a Grip (#corl2024)!
We show that instead of generative models, discriminative models can attain sim2real transfer!
👀🧵👇
We're presenting Jacta: a versatile planner for learning dexterous and whole-body manipulation this week at CoRL!
website jacta-manipulation.github.io…
paper arxiv.org/abs/2408.01258
Our team is presenting work at the Conference on Robot Learning, @corl_conf, in Munich, Germany this week! Learn more about our accepted research — theaiinstitute.com/news/corl…
I'm excited to share Jacta: A Versatile Planner for Learning Dexterous and Whole-body Manipulation.
We use sampling-based planning to bootstrap policy learning methods for manipulation tasks.
My friend, Jan Brüdigam is presenting the work today at CoRL!
jacta-manipulation.github.io…
Simon LC retweeted
Excited to share our new📰, DROP: Dexterous Reorientation via Online Planning!
Overview:
🔹We tackle cube rotation🧊♻️on hardware
🔹DROP is the first 🧊♻️sampling-based MPC demo. No reinforcement learning!
🔹Median 30.5 rotations w/o dropping, max of 81👑🦾
See 🧵below👇
Really cool work on bimanual dexterity!!
Achieving bimanual dexterity with RL + Sim2Real!
toruowo.github.io/bimanual-t…
TLDR - We train two robot hands to twist bottle lids using deep RL followed by sim-to-real. A single policy trained with simple simulated bottles can generalize to drastically different real-world objects.
Simon LC retweeted
Excited to share our latest work, Vision-Language Frontier Maps – a SOTA approach for semantic navigation in robotics. VLFM enables robots to navigate and find objects in novel environments using vision-language foundation models, zero-shot! Accepted to #ICRA2024!
🧵
Simon LC retweeted
want your next robot 🤖 to move like your favorite pet 🐶? youtube videos might be all you need.
checkout our recent work -- SLoMo
paper: rexlab.ri.cmu.edu/papers/slo…
website: slomo-www.github.io/website/
video: youtu.be/bvoM-nBd7lM?si=9f2g…