@inproceedings{9ccdaf9cb477421faf51fbe359525205,
title = "Learning motion planning functions using a linear transition in the C-space: Networks and kernels",
abstract = "Motion planning approaches aided by learning schemes have achieved relevant results in the community, particularly in terms of rendering new paths efficiently and adapting to new environments/situations through encoder-decoder frameworks and latent space configurations. This paper evaluates the feasibility of learning motion planning functions for robot manipulators using a linear transition of the configuration space. Our computational experiments involving a relevant set of learning architectures have shown the feasibility and the efficiency in finding motion planning functions that meet user-defined criteria. Our approach contributes to realizing the practical efficiency to tackle the learning-based motion planning problem. Due to the amenability to parallelization schemes, our approach is potential to tackle larger degrees of freedom.",
keywords = "Kernels, Motion planning, Neural networks, Robot manipulator",
author = "Victor Parque",
note = "Funding Information: This research was supported by JSPS KAKENHI Grant Number 20K11998. Publisher Copyright: {\textcopyright} 2021 IEEE.; 45th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2021 ; Conference date: 12-07-2021 Through 16-07-2021",
year = "2021",
month = jul,
doi = "10.1109/COMPSAC51774.2021.00229",
language = "English",
series = "Proceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1538--1543",
editor = "Chan, {W. K.} and Bill Claycomb and Hiroki Takakura and Ji-Jiang Yang and Yuuichi Teranishi and Dave Towey and Sergio Segura and Hossain Shahriar and Sorel Reisman and Ahamed, {Sheikh Iqbal}",
booktitle = "Proceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021",
}