@inproceedings{0a5e6e85cbd4467499a83d5ee2d7fdec,
title = "Towards higher order fairness functionals for smooth path planning",
abstract = "Smoothness of mobile and vehicle navigation has become relevant to ensure the safety and the comfortability of riding. The robotics community has been able to render smooth trajectories in mobile robots by using non-linear optimization approaches and well-known fairness metrics considering the curvature variations along the path. In this paper, we introduce the possibility of computing smooth paths from observed mobile robot trajectories from higher order non-linear fairness functionals. Our approach is potential to enable the generation of simple and computationally-efficient path planning smoothing for navigation in mobile robots.",
keywords = "curve fitting, fairing, mobile robots, optimization, path smoothing, smoothness functionals",
author = "Victor Parque",
note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 2021 Genetic and Evolutionary Computation Conference, GECCO 2021 ; Conference date: 10-07-2021 Through 14-07-2021",
year = "2021",
month = jul,
day = "7",
doi = "10.1145/3449726.3459430",
language = "English",
series = "GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery, Inc",
pages = "319--320",
booktitle = "GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion",
}