409 citations · 410 across the 3 of their papers we have counts for
5 papers
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…
OmniHang: Learning to Hang Arbitrary Objects using Contact Point Correspondences and Neural Collision Estimation
Yifan You, Lin Shao, Toki Migimatsu +1
In this paper, we explore whether a robot can learn to hang arbitrary objects onto a diverse set of supporting items such as racks or hooks. Endowing robots with such an ability ha…
Object-Centric Task and Motion Planning in Dynamic Environments
Toki Migimatsu, Jeannette Bohg
We address the problem of applying Task and Motion Planning (TAMP) in real world environments. TAMP combines symbolic and geometric reasoning to produce sequential manipulation pla…
Learning to Scaffold the Development of Robotic Manipulation Skills
Lin Shao, Toki Migimatsu, Jeannette Bohg
Learning contact-rich, robotic manipulation skills is a challenging problem due to the high-dimensionality of the state and action space as well as uncertainty from noisy sensors a…
An Empirical Evaluation of Deep Learning on Highway Driving
Brody Huval, Tao Wang, Sameep Tandon +10
Numerous groups have applied a variety of deep learning techniques to computer vision problems in highway perception scenarios. In this paper, we presented a number of empirical ev…