Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Fabrizio Mieli

dblp:41/3554 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot navigation and mapping · 67% Motion planning and robot control · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › path planning › coverage path planning
multi-robot coverage
0.112006
Towards Robust on-line Multi-robot Coverage · ICRA 2006
Robotics › Robot navigation and mapping › coverage control
online coverage
0.112006
Towards Robust on-line Multi-robot Coverage · ICRA 2006
Robotics › Robot navigation and mapping › coverage control
robust coverage
0.112006
Towards Robust on-line Multi-robot Coverage · ICRA 2006
YearPublicationVenuePosition
2006 Towards Robust on-line Multi-robot Coverage
abstract
Area coverage is an important task for mobile robots, with many real-world applications. In many cases, the coverage has to be completed without the use of a map or any a priori knowledge about the area, a process referred-to as on-line coverage. Previous investigations of multi-robot on-line coverage focused on the improved efficiency gained from the use of multiple robots, but did not formally addressed the potential for greater robustness. We present a novel multi-robot on-line coverage algorithm, based on approximate cell decomposition. We analytically show that the algorithm is complete and robust, in that as long as a single robot is able to move, the coverage would be completed. We analyze the assumptions underlying the algorithm requirements and present a number of techniques for executing it in real robots. We show empirical coverage-time results of running the algorithm in two different environments and several group sizes
Noam Hazon, Fabrizio Mieli, Gal A. Kaminka
ICRA2