# Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network

arXiv: https://arxiv.org/abs/1901.10142 · HTML: https://mlsanity.com/paper/1901.10142/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jan 2019.

## Built on by (most cited first, 2 of 2)

- [In-air Knotting of Rope using Dual-Arm Robot based on Deep Learning](https://mlsanity.com/paper/2103.09402/) (2021)
- [Cloth Manipulation Planning on Basis of Mesh Representations with Incomplete Domain Knowledge and Voxel-to-Mesh Estimation](https://mlsanity.com/paper/2103.08137/) (2021)

## Abstract (arXiv)

For dynamic manipulation of flexible objects, we propose an acquisition method of a flexible object motion equation model using a deep neural network and a control method to realize a target state by calculating an optimized time-series joint torque command. By using the proposed method, any physics model of a target object is not needed, and the object can be controlled as intended. We applied this method to manipulations of a rigid object, a flexible object with and without environmental contact, and a cloth, and verified its effectiveness.