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Physics-Based Object 6D-Pose Estimation during Non-Prehensile Manipulation
At any given time during the manipulation of the object, we assume access to the robot joint controls and an image from a camera.
Learning to Efficiently Plan Robust Frictional Multi-Object Grasps
In physical experiments, we find a 13. 7% increase in success rate, a 1. 6x increase in picks per hour, and a 6. 3x decrease in grasp planning time compared to prior work on multi-object grasping.
Parareal with a Learned Coarse Model for Robotic Manipulation
In simulated experiments using the physics engine Mujoco as fine propagator we show that the learned coarse model leads to faster Parareal convergence than a coarse physics-based model.
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