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

Thomas Laurent Peeters

dblp:353/5877 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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 · 64% Multi-agent systems · 28% Reinforcement learning · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
environment mapping
0.712023
Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge · ICRA 2023
Robotics › Robot navigation and mapping › robot mapping › environment modeling
gas distribution mapping
0.712023
Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge · ICRA 2023
Knowledge, reasoning and agents › Multi-agent systems
multi-robot coordination
0.712023
Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge · ICRA 2023
Machine learning › Reinforcement learning
exploration
0.212023
Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge · ICRA 2023
Robotics › Robot navigation and mapping › mobile robot navigation › navigation planning
informative path planning
0.212023
Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge · ICRA 2023

Methods — techniques the papers use, named apart from their topics

information-gain navigation · 0.7high-fidelity simulation · 0.7
YearPublicationVenuePosition
2023 Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge
abstract
Environmental monitoring and mapping operations are an essential tool to combat climate change. An important branch of this domain concerns the construction of reliable gas maps. Adaptive navigation strategies coupled with multi-robot systems improve the outcome of an environmental mapping mission by focusing more efficiently on informative areas. This direction is yet to be explored in the context of gas mapping, which presents peculiar challenges due to the hard-to-sense and expensive-to-model nature of the underlying phenomenon. In this paper, we introduce the application of a multi-robot system to a gas mission with severe time constraints. We study the impact of information-based navigation strategies, coupled with increasing levels of coordination among the robots, on information gathering and consequent map reconstruction performance. We also focus on proposing solutions that inject additional knowledge into the system to enhance the final mapping outcome. We tested the strategies through extensive high-fidelity simulation experiments, and we compared the proposed approaches to three relevant baseline methods.
Chiara Ercolani, Shashank Mahendra Deshmukh, Thomas Laurent Peeters, Alcherio Martinoli
ICRA3