Simar Kareer
@simar_kareer
Research Intern at π | PhD at GT
Introducing EgoMimic - just wear a pair of Project Aria @meta_aria smart glasses 👓 to scale up your imitation learning datasets! Check out what our robot can do. A thread below👇
Imagine robots learning new skills—without any robot data. Today, we're excited to release EgoZero: our first steps in training robot policies that operate in unseen environments, solely from data collected through humans wearing Aria smart glasses. 🧵👇
Imitation learning has seen great success, but IL policies still struggle with OOD observations We designed a 3D backbone, Adapt3R, that can combine with your favorite IL algorithm to enable zero-shot generalization to unseen embodiments and camera viewpoints!
Mobile manipulation is hard, and generalizing to new environments is even harder. We take a stab at both in our latest release, where our robots clean Airbnbs they've never been to!
We got a robot to clean up homes that were never seen in its training data! Our new model, π-0.5, aims to tackle open-world generalization. We took our robot into homes that were not in the training data and asked it to clean kitchens and bedrooms. More below⤵️
We are excited to share new experiments with AgiBot @AgiBot_zhiyuan on multi-task, multi-embodiment VLAs! With one model that can perform many tasks with both two-finger grippers and multi-fingered hands, we take another step toward one model for all robots and tasks.
Introducing Hi Robot – Hierarchical Interactive Robot Our first step at @physical_int towards teaching robots to listen and think harder. A 🧵 on how we make robots more steerable 👇
Thanks @meta_aria @AIatMeta for featuring our work!
Prof. Danfei Xu (@danfei_xu) and the Robot Learning and Reasoning Lab (RL2) present EgoMimic. EgoMimic is a full-stack framework that scales robot manipulation through egocentric-view human demonstrations via Project Aria glasses. 🔖Blog post: ai.meta.com/blog/egomimic-… 🔗Github:…
Introducing Gaze-LLE, a new model for gaze target estimation built on top of a frozen visual foundation model! Gaze-LLE achieves SOTA results on multiple benchmarks while learning minimal parameters, and shows strong generalization paper: arxiv.org/abs/2412.09586
We have a new ICML paper! Adaptive Horizon Actor Critic (AHAC). Joint work with @krishpopdesu @xujie7979 @eric_heiden @animesh_garg AHAC is a first-order model-based RL algorithm that learns high-dimensional tasks in minutes and outperforms PPO by 40%. 🧵(1/4)
🤖 Inspiring the Next Generation of Roboticists! 🎓 Our lab had an incredible opportunity to demo our robot learning systems to local K-12 students for the National Robotics Week program @GTrobotics . A big shout-out to @saxenavaibhav11 @simar_kareer @pranay_mathur17 for hosting…
If you’re looking to study domain adaptation on videos, definitely try out our paper / code with reproducibility certification! github.com/SimarKareer/Un…
New #ReproducibilityCertification: We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline Simar Kareer, Vivek Vijaykumar, Harsh Maheshwari et al. openreview.net/forum?id=10R6i… #unifiedvideoda #adaptation #benchmarking