Fit2Form: 3D Generative Model for Robot Gripper Form Design

Understand

The 3D shape of a robot's end-effector plays a critical role in determining it's functionality and overall performance.

• Many industrial applications rely on task-specific gripper designs to ensure the system's robustness and accuracy.
• However, the process of manual hardware design is both costly and time-consuming, and the quality of the resulting design is dependent on the engineer's experience and domain expertise, which can easily be out-dated or inaccurate.
• The goal of this work is to use machine learning algorithms to automate the design of task-specific gripper fingers.