6 papers
Learning to Build by Building Your Own Instructions
Aaron Walsman, Muru Zhang, Adam Fishman +2
Structural understanding of complex visual objects is an important unsolved component of artificial intelligence. To study this, we develop a new technique for the recently propose…
OptiGrasp: Optimized Grasp Pose Detection Using RGB Images for Warehouse Picking Robots
Soofiyan Atar, Yi Li, Markus Grotz +3
In warehouse environments, robots require robust picking capabilities to manage a wide variety of objects. Effective deployment demands minimal hardware, strong generalization to n…
PerAct2: Benchmarking and Learning for Robotic Bimanual Manipulation Tasks
Markus Grotz, Mohit Shridhar, Tamim Asfour +1
Bimanual manipulation is challenging due to precise spatial and temporal coordination required between two arms. While there exist several real-world bimanual systems, there is a l…
URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images
Zoey Chen, Aaron Walsman, Marius Memmel +6
Constructing simulation scenes that are both visually and physically realistic is a problem of practical interest in domains ranging from robotics to computer vision. This problem…
ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu +3
Model-free control strategies such as reinforcement learning have shown the ability to learn control strategies without requiring an accurate model or simulator of the world. While…
STOW: Discrete-Frame Segmentation and Tracking of Unseen Objects for Warehouse Picking Robots
Yi Li, Muru Zhang, Markus Grotz +2
Segmentation and tracking of unseen object instances in discrete frames pose a significant challenge in dynamic industrial robotic contexts, such as distribution warehouses. Here,…