Computation Sharing in Distributed Robotic Systems: A Case Study on SLAM

• Type: Article in International Scientific Journal
• Date: 2015

Authors

Bruno Duarte Gouveia (Author) Other; David Portugal (Author) Other; Daniel Castro Silva (Author) FEUP; Lino Marques (Author) Other

Journal

Title: IEEE Transactions on Automation Science and Engineering

Vol. 12 No. 2

Pages: 410-422

ISSN: 1545-5955

Publisher: IEEE

Indexing

ISI Web of Knowledge - 28 Citations

ISI Web of Science

Scopus - 3 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-00A-B83

DOI: 10.1109/tase.2014.2357216

Abstract (EN): Aiming at increasing team efficiency, mobile robots may act as a node of a Robotic Cluster to assist their teammates in computationally demanding tasks. Having this in mind, we propose two distributed architectures for the Simultaneous Localization And Mapping (SLAM) problem, our main case study. The analysis focuses especially on the efficiency gain that can be obtained. It is shown that the proposed architectures enable us to raise the workload up to values that would not be possible in a single robot solution, thus gaining in localization precision and map accuracy. Furthermore, we assess the impact of network bandwidth. All the results are extracted from frequently used SLAM datasets available in the robotics community and a real world testbed is described to show the potential of using the proposed philosophy. Note to Practitioners-Multirobot systems commonly suffer from limited computational resources, which interferes with the ability of each individual robot to finish the task underway. Generally in these scenarios, the use of the available computational power varies over time. Hence, based on the Robotic Clusters concept, we propose to allocate computational resources available in the multirobot system to solve computationally hard problems arising in the real world. As a case study, we propose two architectures for a solidary multirobot system engaged in a SLAM task. In this paper, we thoroughly discuss the tradeoffs of the architectures proposed in terms of efficiency, complexity, exchange of data, load balancing and SLAM performance.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13