2.3k citations · 4.7k across the 84 of their papers we have counts for
10 papers · 1 filter
Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning
Jingyun Yang, Max Sobol Mark, Brandon Vu +3
The pre-train and fine-tune paradigm in machine learning has had dramatic success in a wide range of domains because the use of existing data or pre-trained models on the internet…
ShaSTA-Fuse: Camera-LiDAR Sensor Fusion to Model Shape and Spatio-Temporal Affinities for 3D Multi-Object Tracking
Tara Sadjadpour, Rares Ambrus, Jeannette Bohg
3D multi-object tracking (MOT) is essential for an autonomous mobile agent to safely navigate a scene. In order to maximize the perception capabilities of the autonomous agent, we…
EquivAct: SIM(3)-Equivariant Visuomotor Policies beyond Rigid Object Manipulation
Jingyun Yang, Congyue Deng, Jimmy Wu +3
If a robot masters folding a kitchen towel, we would expect it to master folding a large beach towel. However, existing policy learning methods that rely on data augmentation still…
AO-Grasp: Articulated Object Grasp Generation
Carlota Parés Morlans, Claire Chen, Yijia Weng +6
We introduce AO-Grasp, a grasp proposal method that generates 6 DoF grasps that enable robots to interact with articulated objects, such as opening and closing cabinets and applian…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
KITE: Keypoint-Conditioned Policies for Semantic Manipulation
Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh +1
While natural language offers a convenient shared interface for humans and robots, enabling robots to interpret and follow language commands remains a longstanding challenge in man…
The ObjectFolder Benchmark: Multisensory Learning with Neural and Real Objects
Ruohan Gao, Yiming Dou, Hao Li +5
We introduce the ObjectFolder Benchmark, a benchmark suite of 10 tasks for multisensory object-centric learning, centered around object recognition, reconstruction, and manipulatio…
TidyBot: Personalized Robot Assistance with Large Language Models
Jimmy Wu, Rika Antonova, Adam Kan +6
For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios. In this work, we investigate persona…
CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objects
Nick Heppert, Muhammad Zubair Irshad, Sergey Zakharov +5
We present CARTO, a novel approach for reconstructing multiple articulated objects from a single stereo RGB observation. We use implicit object-centric representations and learn a…
Text2Motion: From Natural Language Instructions to Feasible Plans
Kevin Lin, Christopher Agia, Toki Migimatsu +2
We propose Text2Motion, a language-based planning framework enabling robots to solve sequential manipulation tasks that require long-horizon reasoning. Given a natural language ins…