409 citations · 725 across the 12 of their papers we have counts for
4 papers · 1 filter
Active Task Randomization: Learning Robust Skills via Unsupervised Generation of Diverse and Feasible Tasks
Kuan Fang, Toki Migimatsu, Ajay Mandlekar +2
Solving real-world manipulation tasks requires robots to have a repertoire of skills applicable to a wide range of circumstances. When using learning-based methods to acquire such…
STAP: Sequencing Task-Agnostic Policies
Christopher Agia, Toki Migimatsu, Jiajun Wu +1
Advances in robotic skill acquisition have made it possible to build general-purpose libraries of learned skills for downstream manipulation tasks. However, naively executing these…
Category-Independent Articulated Object Tracking with Factor Graphs
Nick Heppert, Toki Migimatsu, Brent Yi +2
Robots deployed in human-centric environments may need to manipulate a diverse range of articulated objects, such as doors, dishwashers, and cabinets. Articulated objects often com…
Symbolic State Estimation with Predicates for Contact-Rich Manipulation Tasks
Toki Migimatsu, Wenzhao Lian, Jeannette Bohg +1
Manipulation tasks often require a robot to adjust its sensorimotor skills based on the state it finds itself in. Taking peg-in-hole as an example: once the peg is aligned with the…