University of Oulu

O. Çağırıcı, Y. Bahoo and S. M. LaValle, "Bouncing Robots in Rectilinear Polygons," 2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR), Międzyzdroje, Poland, 2022, pp. 193-198, doi: 10.1109/MMAR55195.2022.9874340

Bouncing robots in rectilinear polygons

Saved in:
Author: Çağırıcı, Onur1; Bahoo, Yeganeh1; LaValle, Steven M.2
Organizations: 1Department of Computer Science, Ryerson University, Toronto, Canada
2Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
Persistent link:
Language: English
Published: IEEE, 2022
Publish Date: 2023-04-14


In this paper, we describe a bouncing strategy (smart strategy) for a mobile robot that uses one bit of memory for feedback, and guarantees that the robot will traverse all the rooms (and doorways) of a 2D environment. The environment is modeled as a rectilinear polygon (also called orthogonal polygon), and the rooms and the doorways are defined by the decomposition algorithm we describe. Such a decomposition helps the robot to not go back to a room after leaving. We also define the notion of “virtual doors” that have the ability to let the robot through, or make the robot bounce from them. We compared three different types of bouncing rules: smart, random, billiard. The smart strategy grantees to reach to target. Although the random strategy on average behaves the same as the smart strategy, there are rectilinear polygons in which the robot cannot reach the target in the expected time steps. On the other hand, the billiard bouncing strategy can cause the robot to become trapped.

see all

ISBN: 978-1-6654-6858-9
ISBN Print: 978-1-6654-6859-6
DOI: 10.1109/mmar55195.2022.9874340
Host publication: 2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)
Conference: International Conference on Methods and Models in Automation and Robotics
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This research has been supported by the Ryerson University Faculty of Science Dean’s Research Fund.
Copyright information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.