In this work, we propsoe a learning framework for a manipulation technique to bin picking, named Dig-Grasping, which aims at singulating and simultaneously picking the objects one by one from a random clutter. Dig-grasping illustrates a way of grasping through a physical interaction between the robot's gripper and object clutter, realized as a digging operation along a straight line. A gripper designed for this technique is capable of changing relative digit lengths such that the object being digged will not collide with the other finger. This repository provides the PyTorch implementation for
You can find additional resources on [Github]. (Coming Soon) Includes:
- The Benchmark
- Paper code (architectures, losses, dataloaders, etc.)
- Model weights