Tool Shape Optimization through Backpropagation of Neural Network

Kento Kawaharazuka; Toru Ogawa; Cota Nabeshima

IROS 2020poster8 citations

Tool Shape Optimization through Backpropagation of Neural Network

Kento Kawaharazuka, Toru Ogawa, Cota Nabeshima

Abstract

When executing a certain task, human beings can choose or make an appropriate tool to achieve the task. This research especially addresses the optimization of tool shape for robotic tool-use. We propose a method in which a robot obtains an optimized tool shape, tool trajectory, or both, depending on a given task. The feature of our method is that a transition of the task state when the robot moves a certain tool along a certain trajectory is represented by a deep neural network. We applied this method to object manipulation tasks on a 2D plane, and verified that appropriate tool shapes are generated by using this novel method.

BibTeX

@inproceedings{iros2020_toolshapeoptimiz,
  title = {Tool Shape Optimization through Backpropagation of Neural Network},
  author = {Kento Kawaharazuka and Toru Ogawa and Cota Nabeshima},
  booktitle = {IROS 2020},
  year = {2020}
}