Abstract: The prevalent approach to object manipulation is based on the availability of explicit 3D object models. By estimating the pose of such models in a scene, a robot can readily reason about how to pick up an object, place it in a stable position, or avoid collisions. Unfortunately, assuming the availability of object models constrains the settings in which a robot can operate, and noise in estimating a model’s pose can result in brittle manipulation performance.
Wednesday, October 5, 2022 – 12:15 to 13:15
Marcus Nanotechnology Building 1116-1118 | 345 Ferst Drive | Atlanta GA | 30332
Featuring: Dieter Fox – Professor; Allen School of Computer Science & Engineering, University of Washington and Leader; NVIDIA Seattle Robotics Lab.