356 citations · 1.5k across the 30 of their papers we have counts for
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Self-Supervised Correspondence in Visuomotor Policy Learning
Peter Florence, Lucas Manuelli, Russ Tedrake
In this paper we explore using self-supervised correspondence for improving the generalization performance and sample efficiency of visuomotor policy learning. Prior work has prima…
kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation
Lucas Manuelli, Wei Gao, Peter Florence +1
We would like robots to achieve purposeful manipulation by placing any instance from a category of objects into a desired set of goal states. Existing manipulation pipelines typica…
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Jeong Joon Park, Peter Florence, Julian Straub +2
Computer graphics, 3D computer vision and robotics communities have produced multiple approaches to representing 3D geometry for rendering and reconstruction. These provide trade-o…