Marwanon / Learning-Pick-to-Place-Objects-in-a-cluttered-scene-using-deep-reinforcement-learningView on GitHub
roposes an efficient grasp-to-place strategy for robotic manipulation in sparse environments using a deep Q-network. Requires less computation and time, generalizes well across scenarios, and achieves optimal grasp points via trial-and-error learning. Demonstrated effectiveness with a UR5 robotic arm and Parallel-jaw gripper.
☆7Feb 24, 2024Updated 2 years ago
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