Grasping of an object by a robot based on grasp strategy determined using machine learning model(s)

A robot picks up objects by using a machine learning model to choose the best grasping method. The model analyzes 3D visual data from the robot's camera, which can include 2D images, to select a specific strategy, such as the direction, type of grip, or how much force to apply.

Why it matters: Machine learning models for robotic vision and grasp planning have advanced significantly since 2021. Training and deploying robust models for complex grasp strategy selection is now more feasible and effective.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedRobot, vision system, machine learning software

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