A U-Net-style CNN trained on synthetic multi-modal grasp data from the Genesis simulator enables a real quadruped robot to navigate to and precisely grasp objects in a loco-manipulation task.
Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach,
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Optimizing Grasping in Legged Robots: A Deep Learning Approach to Loco-Manipulation
A U-Net-style CNN trained on synthetic multi-modal grasp data from the Genesis simulator enables a real quadruped robot to navigate to and precisely grasp objects in a loco-manipulation task.