This project introduces DYNAMO-GRASP, a novel approach to the challenge of suction grasp point detection. By leveraging the power of physics-based simulation and data-driven modeling, DYNAMO-GRASP is capable of accounting for object dynamics during the grasping process. This significantly enhances a robot's ability to handle unseen objects in real-world scenarios. Our method was benchmarked against established approaches through comprehensive evaluations in both simulated and real-world environments. It outperformed the alternatives by achieving a success rate of 98% in diverse simulated picking tasks and 80% in real-world, adversarially-designed scenarios. DYNAMO-GRASP demonstrates a strong ability to adapt to complex and unexpected object dynamics, offering robust generalization to real-world challenges. The results of this research pave the way for more reliable and resilient robotic manipulation in intricate real-world situations.
This repository provides the codebase for collecting data through simulation. These scripts will help users to generate their own datasets, further enhancing the extensibility and usefulness of DYNAMO-GRASP.
For more information please refer to our project website
For installation and usage instructions, please refer to the documentation