A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots

Victor Parque

doi:10.1109/CASE49439.2021.9551561

A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots

Victor Parque

Graduate School of Creative Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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 evaluate the possibility of computing smooth paths from input reference trajectories by using higher order non-linear fairness functionals. Our approach is potential to enable the generation of simple and computationally-efficient path planning and smoothing for navigation in mobile robots.

Original language	English
Title of host publication	2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
Publisher	IEEE Computer Society
Pages	1568-1573
Number of pages	6
ISBN (Electronic)	9781665418737
DOIs	https://doi.org/10.1109/CASE49439.2021.9551561
Publication status	Published - 2021 Aug 23
Event	17th IEEE International Conference on Automation Science and Engineering, CASE 2021 - Lyon, France Duration: 2021 Aug 23 → 2021 Aug 27

Publication series

Name	IEEE International Conference on Automation Science and Engineering
Volume	2021-August
ISSN (Print)	2161-8070
ISSN (Electronic)	2161-8089

Conference

Conference	17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Country/Territory	France
City	Lyon
Period	21/8/23 → 21/8/27

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/CASE49439.2021.9551561

Cite this

A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots. / Parque, Victor.
2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021. IEEE Computer Society, 2021. p. 1568-1573 (IEEE International Conference on Automation Science and Engineering; Vol. 2021-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Parque, V 2021, A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots. in 2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021. IEEE International Conference on Automation Science and Engineering, vol. 2021-August, IEEE Computer Society, pp. 1568-1573, 17th IEEE International Conference on Automation Science and Engineering, CASE 2021, Lyon, France, 21/8/23. https://doi.org/10.1109/CASE49439.2021.9551561

@inproceedings{7719f879e0cc44af9ed65a5d1f793f3f,

title = "A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots",

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 evaluate the possibility of computing smooth paths from input reference trajectories by using higher order non-linear fairness functionals. Our approach is potential to enable the generation of simple and computationally-efficient path planning and smoothing for navigation in mobile robots.",

author = "Victor Parque",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 17th IEEE International Conference on Automation Science and Engineering, CASE 2021 ; Conference date: 23-08-2021 Through 27-08-2021",

year = "2021",

month = aug,

day = "23",

doi = "10.1109/CASE49439.2021.9551561",

language = "English",

series = "IEEE International Conference on Automation Science and Engineering",

publisher = "IEEE Computer Society",

pages = "1568--1573",

booktitle = "2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021",

}

TY - GEN

T1 - A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots

AU - Parque, Victor

PY - 2021/8/23

Y1 - 2021/8/23

N2 - 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 evaluate the possibility of computing smooth paths from input reference trajectories by using higher order non-linear fairness functionals. Our approach is potential to enable the generation of simple and computationally-efficient path planning and smoothing for navigation in mobile robots.

AB - 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 evaluate the possibility of computing smooth paths from input reference trajectories by using higher order non-linear fairness functionals. Our approach is potential to enable the generation of simple and computationally-efficient path planning and smoothing for navigation in mobile robots.

UR - http://www.scopus.com/inward/record.url?scp=85116974837&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85116974837&partnerID=8YFLogxK

U2 - 10.1109/CASE49439.2021.9551561

DO - 10.1109/CASE49439.2021.9551561

M3 - Conference contribution

AN - SCOPUS:85116974837

T3 - IEEE International Conference on Automation Science and Engineering

SP - 1568

EP - 1573

BT - 2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021

PB - IEEE Computer Society

T2 - 17th IEEE International Conference on Automation Science and Engineering, CASE 2021

Y2 - 23 August 2021 through 27 August 2021

ER -

A Study of Fairness Functionals for Smooth Path Planning in Mobile Robots

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this