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AUTOLab

AUTOLab

@AUTOLab_Cal

Automation Lab @Cal @UCBerkeley directed by Prof. @Ken_Goldberg

Berkeley, CA Bergabung Nisan 2016
100 Mengikuti310 Pengikut
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Mathieu Blondel
Mathieu Blondel@mblondel_ml·
JAXopt v0.2 is out! github.com/google/jaxopt/… The main highlight of this release is an implementation of OSQP, a GPU-friendly quadratic programming solver. Our implementation of course supports implicit differentiation ;) Thanks to our intern Louis Béthune for the hard work.
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Ashwin Balakrishna
Ashwin Balakrishna@ashwinb96·
Interested in safe and robust learning for control? Come check out our NeurIPS 2021 Workshop on Safe and Robust Control of Uncertain Systems (Website: sites.google.com/view/safe-robu……) on 12/13 from 8 AM - 4 PM PST! You can register here: neurips.cc.
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Max Fu
Max Fu@letian_fu·
Can a robot teach itself to grasp complex objects? Learned Efficient Grasp Sets (LEGS) can help robots efficiently learn to grasp novel, out-of-distribution objects. Research from @AUTOLab_Cal @UCBerkeley. Paper, website: sites.google.com/view/legs-exp-… (1/8)
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Ken Goldberg
Ken Goldberg@Ken_Goldberg·
Robots can be designed to be symbiotic with workers, freeing us to focus on the myriad of tasks AI can’t do well. Proud that this is an axiom for @AmbiRobotics.
AmbiRobotics@AmbiRobotics

We always ask ourselves: how does this make the user feel? We remain rooted in our core beliefs as we rapidly deploy #AI-powered #sorting systems throughout the #supplychain. We see #robots as smart tools, empowering people to handle more than ever before.

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Mark Presten
Mark Presten@mark_presten_·
What’s the future of food? Polyculture farming is more sustainable than monoculture, but requires more labor. Could robots help? New results w/ AlphaGarden using “Real2Sim2Real” learning from @AUTOLab_Cal @UCBerkeley. Data, paper, and presentation: sites.google.com/berkeley.edu/a… (1/9)
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Ken Goldberg
Ken Goldberg@Ken_Goldberg·
Unlike fly-fishing, shuffleboard, and bowling, Planar Robot Casting allows self-supervised learning. This real-world robot control problem includes nondeterminism, surface friction, and deformable materials, and it's relatively easy to set up; hoping others study it also:
Raven Huang@RavenHuang4

Planar Robot Casting for deformable materials aims to achieve a desired final state from one dynamic launching action. Our work from @AUTOLab_Cal @Berkeley_AI learn it using a self-supervised “Real2Sim2Real” framework. Data, paper, and presentation: tinyurl.com/robotcast (1/8)

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Raven Huang
Raven Huang@RavenHuang4·
Planar Robot Casting for deformable materials aims to achieve a desired final state from one dynamic launching action. Our work from @AUTOLab_Cal @Berkeley_AI learn it using a self-supervised “Real2Sim2Real” framework. Data, paper, and presentation: tinyurl.com/robotcast (1/8)
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Ken Goldberg
Ken Goldberg@Ken_Goldberg·
Fun to be in London with @jeff_ichnowski @ashwinb96 @brthananjeyan @ryan_hoque @yahavigal @AleEscontrela & Justin Kerr from @AUTOLab_Cal checking out @anickali’s elegant floating robots @tatemodern, eating Yorkshire pudding and looking fwd to robotics rendezvous this week:
Conference on Robot Learning@corl_conf

The Conference on #Robot #Learning 2021 will be held on Nov 8-11 in London, UK & virtually. Exciting new changes, including: - both regular and blue sky paper submission types, and - use of #openreview June 18th is the submission date! Find out more: robot-learning.org

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Sergey Levine
Sergey Levine@svlevine·
Why is generalization hard in RL? Can "just adding more data" fix it? Turns out that in general, the answer is no. In a new blog post, @its_dibya discusses this question: bair.berkeley.edu/blog/2021/11/0… Trying to generalize induces a POMDP, even if the problem is an MDP!
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Berkeley School of Information
Berkeley School of Information@BerkeleyISchool·
📝 The graduate admission application is open! 📆 Deadlines: ✔️ PhD: 12/1/21 ✔️ MIMS: 1/6/22 ✔️ 5th Year MIDS: Early (app fee waived!) - 11/4/21; Final - 3/2/22 ✔️ MIDS & MICS: rolling throughout the year! Grad app: bit.ly/3zsoOVZ
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Ken Goldberg
Ken Goldberg@Ken_Goldberg·
“…What started in 2017 as an email discussion and later a Facebook Group has grown into a global movement of 3,800 members in more than 50 countries. Black in AI works in academics, advocacy, entrepreneurship, financial support, and summer research programs.”
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Stephen James
Stephen James@stepjamUK·
'basketball_in_hoop'; one of many new tasks joining the #RLBench family of 100+ tasks in V1.2. Coming early November! 🤖 RLBench is still the hardest manipulation sim-benchmark to date due to its large-scale focus on vision, sparse rewards, and multi-stage tasks.
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Jelajahi

@obviousvc @UCBerkeley @Ini_fadelli @ToyotaResearch @techxplore_com @AmbiRobotics @Berkeley_AI @jeff_ichnowski