UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Task-Consistent Path Planning for Mobile 3D Printing

Sustarevas, J; Kanoulas, D; Julier, S; (2021) Task-Consistent Path Planning for Mobile 3D Printing. In: Proceedings of the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021). (pp. pp. 2143-2150). Institute of Electrical and Electronics Engineers (IEEE) Green open access

[thumbnail of P34__Sustarevas__2021__IROS.pdf]
Preview
Text
P34__Sustarevas__2021__IROS.pdf - Accepted Version

Download (5MB) | Preview

Abstract

In this paper, we explore the problem of task-consistent path planning for printing-in-motion via Mobile Manipulators (MM). MM offer a potentially unlimited planar workspace and flexibility for print operations. However, most existing methods have only mobility to relocate an arm which then prints while stationary. In this paper we present a new fully autonomous path planning approach for mobile material deposition. We use a modified version of Rapidly-exploring Random Tree Star (RRT*) algorithm, which is informed by a constrained Inverse Reachability Map (IRM) to ensure task consistency. Collision avoidance and end-effector reachability are respected in our approach. Our method also detects when a print path cannot be completed in a single execution. In this case it will decompose the path into several segments and reposition the base accordingly.

Type: Proceedings paper
Title: Task-Consistent Path Planning for Mobile 3D Printing
Event: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
ISBN-13: 978-1-6654-1714-3
Open access status: An open access version is available from UCL Discovery
Publisher version: https://doi.org/10.1109/IROS51168.2021.9635916
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Three-dimensional printing, Path planning, End effectors, Task analysis, Collision avoidance, Intelligent robots
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10133188
Downloads since deposit
168Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item