GenORM: Generalizable One-shot Rope Manipulation with Parameter-Aware Policy
This addresses the challenge of adapting to various deformable ropes in robotics, though it is incremental as it builds on existing simulation and parameter estimation methods.
The paper tackles the problem of rope manipulation requiring extensive real-world demonstrations by introducing GenORM, a framework that enables manipulation of different deformable ropes with just one real-world demonstration, achieving improvements of 62% for in-domain ropes and 15% for out-of-distribution ropes in simulation, and 26% in real-world tests.
Due to the inherent uncertainty in their deformability during motion, previous methods in rope manipulation often require hundreds of real-world demonstrations to train a manipulation policy for each rope, even for simple tasks such as rope goal reaching, which hinder their applications in our ever-changing world. To address this issue, we introduce GenORM, a framework that allows the manipulation policy to handle different deformable ropes with a single real-world demonstration. To achieve this, we augment the policy by conditioning it on deformable rope parameters and training it with a diverse range of simulated deformable ropes so that the policy can adjust actions based on different rope parameters. At the time of inference, given a new rope, GenORM estimates the deformable rope parameters by minimizing the disparity between the grid density of point clouds of real-world demonstrations and simulations. With the help of a differentiable physics simulator, we require only a single real-world demonstration. Empirical validations on both simulated and real-world rope manipulation setups clearly show that our method can manipulate different ropes with a single demonstration and significantly outperforms the baseline in both environments (62% improvement in in-domain ropes, and 15% improvement in out-of-distribution ropes in simulation, 26% improvement in real-world), demonstrating the effectiveness of our approach in one-shot rope manipulation.