We tested on 6 robot domains and transferred one learned policy to real hardware. Project website: sites.google.com/view/cosil-cor…. Joint work w/ Andrea Baisero @DianWang1007 Chris Amato Robert Platt at Lab for Learning and Planning in Robotics Helping Hands Lab @ Northeastern

I am looking for a PhD student to start in Fall 2023 at Khoury College of Computer Sciences focusing on the direction of 3D vision. Applicants from underrepresented groups are particularly welcome, where the college provides two-year fellowship support (domestic students only). Deadline is Dec 15.

I'm looking for PhD students for Fall 2023 to work at the intersection of Robotic Manipulation, Imitation Learning, and RL. I'm particularly interested in applying novel neural models like geometric DL. Apply by 12/15. Khoury College of Computer Sciences Helping Hands Lab @ Northeastern

Looking for an easy-to-read review paper on Grasp Learning? I just wrote one for Annual Reviews that I'm excited about. Check it out: arxiv.org/abs/2211.04895

We have 2 papers in the main conference #NeurIPS2022. Poster: Wed 5-7 Shield Decentralization for Safe Multi-Agent Reinforcement Learning neurips.cc/virtual/2022/p… Poster: Thurs 5-7 Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning: neurips.cc/virtual/2022/p…

I'll be presenting our #NeurIPS poster tomorrow on Wed 11-1am, poster session 3. Please come by and check it out!

Excited to share our new SOTA grasp method in the Sim-to-Real Robot Learning Workshop at #CoRL2022. I will present the poster tomorrow 13:30-14 and 14:30-15:15 at Eng 405-460. Our work proposes a novel grasp representation as the graph edge and an SE(3)-equivariant model. 1/

Very excited to share our work in the #CoRL2022 Workshop on Sim-to-Real Robot Learning! Our work leverages a novel simulation-based 3D data augmentation method and equivariant networks, helping achieve high data efficiency in imitation learning for robotic manipulation. 1/n

This work is led by @saulbadman12 @DianWang1007, with @GuanangS, David Klee, Xupeng Zhu, Robin Walters, Robert Platt, Helping Hands Lab @ Northeastern. The full version paper: arxiv.org/pdf/2211.00194. Full video: youtube.com/watch?v=UHUmq-….

Interested in partial observability? Come to my online poster session at @CoRL2022 (online session 2, Sunday, Dec 18, 7:30-8.00 AM, Auckland time, i.e., Saturday, Dec 17, 1:30 - 2:00 PM, EST time) w/ Robert Platt Chris Amato @DianWang1007 @AndreaBaisero Lab for Learning and Planning in Robotics Helping Hands Lab @ Northeastern.

Hello world! The Boston Symmetry Group (pun intended) organizes events to foster community amongst Boston-area researchers and practitioners working on symmetry + machine learning. Organizers: Stefanie Jegelka Hannah Lawrence Derek Lim Jung Yeon Park Robin Walters

Congrats to my PhD student Sammie Katt for passing his defense titled "Bayesian Partial Observable Reinforcement Learning." Very cool work, Sammie! (with Frans Oliehoek, Robert Platt, and Lawson Wong).

Registration is now open for Boston Symmetry Day on April 7th! We have an exciting lineup of speakers (Mario Geiger, Prof. Tess Smidt S Gortler, E Grigsby, Robert Platt, Shubhendu Trivedi) + more to come. Sign up here: forms.gle/8gZUh1BRL2FFat…

#ICLR24 We proposed FourTran, a very sample-efficient 3D manipulation pick-place model. 1. It can learn a nontrivial 3D policy with less than 10 demos. 2. It represents 3D action distribution in Fourier Space. Check it in the Poster Session 4 at 4:30 PM Vienna time (10:30 EDT)

Transporter network is great for robotic pick-place, but how to use it in 3D where rotating the kernel for entire SO(3) is infeasible? Our work performs cross correlation in Fourier space to facilitate reasoning over SO(3). Check out at #ICLR2024, Robin Walters is presenting!

Instead of inferring a desired object pose directly, this method "imagines" a reconstruction of the entire scene in the target pose. Surprisingly, we find that this improves sample efficiency, even though we are inferring more information.

Not only is this an interesting approach, but it works great! Outperforms everything we benchmarked against.