Müller S, Müller T, Ahmed A, Gross HM. Laser-Based Door Localization for Autonomous Mobile Service Robots.
SENSORS (BASEL, SWITZERLAND) 2023;
23:s23115247. [PMID:
37299973 DOI:
10.3390/s23115247]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 05/16/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023]
Abstract
For autonomous mobile service robots, closed doors that are in their way are restricting obstacles. In order to open doors with on-board manipulation skills, a robot needs to be able to localize the door's key features, such as the hinge and handle, as well as the current opening angle. While there are vision-based approaches for detecting doors and handles in images, we concentrate on analyzing 2D laser range scans. This requires less computational effort, and laser-scan sensors are available on most mobile robot platforms. Therefore, we developed three different machine learning approaches and a heuristic method based on line fitting able to extract the required position data. The algorithms are compared with respect to localization accuracy with help of a dataset containing laser range scans of doors. Our LaserDoors dataset is publicly available for academic use. Pros and cons of the individual methods are discussed; basically, the machine learning methods could outperform the heuristic method, but require special training data when applied in a real application.
Collapse