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Multi-fingered Robotic Hand Grasping in Cluttered Environments through Hand-object Contact Semantic Mapping
The integration of optimization method and generative models has significantly advanced dexterous manipulation techniques for five-fingered hand grasping.
A Collision-Aware Cable Grasping Method in Cluttered Environment
We introduce a Cable Grasping-Convolutional Neural Network designed to facilitate robust cable grasping in cluttered environments.
A Closed-Loop Multi-perspective Visual Servoing Approach with Reinforcement Learning
Traditional visual servoing methods suffer from serving between scenes from multiple perspectives, which humans can complete with visual signals alone.
Towards Precise Model-free Robotic Grasping with Sim-to-Real Transfer Learning
In physical robotic experiments, our grasping framework grasped single known objects and novel complex-shaped household objects with a success rate of 90. 91%.
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