Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Minimum-violation scLTL motion planning for mobility-on-demand

Minimum-violation scLTL motion planning for mobility-on-demand

Thumbnail Image
Download
Name

ICRA_2017.pdf

Size

2.32 MB

Format

Adobe PDF

Checksum (MD5)

7d43d55990527481428469d99e582011

Download all files submitted through automated deposit
sword-2018-10-16.original.zip (2.24 MB)
Author(s)
Tumova, Jana
•
Belta, Calin
•
Vasile, Cristian-Ioan
•
Karaman, Sertac
•
Rus, Daniela L
Date Issued
May 2017
Journal
2017 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Vasile, Cristian-Ioan, et al. “Minimum-Violation ScLTL Motion Planning for Mobility-on-Demand.” 2017 IEEE International Conference on Robotics and Automation (ICRA), 29 May -3 June, 2017, Singapore, IEEE, 2017, pp. 1481–88. © 2017 IEEE.
Version
Author's final manuscript
Abstract
This work focuses on integrated routing and motion planning for an autonomous vehicle in a road network. We consider a problem in which customer demands need to be met within desired deadlines, and the rules of the road need to be satisfied. The vehicle might not, however, be able to satisfy these two goals at the same time. We propose a systematic way to compromise between delaying the satisfaction of the given demand and violating the road rules. We utilize scLTL formulas to specify desired behavior and develop a receding horizon approach including a periodically interacting routing algorithm and a RRT*-based motion planner. The proposed solution yields a provably minimum-violation trajectory. An illustrative case study is included.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/118835
DOI of Published Version
https://doi.org/10.1109/ICRA.2017.7989177
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.