Jelle Juhl

dblp:246/7774 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—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
Motion planning and robot control · 81% Multi-agent systems · 19%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › multi-robot control
multi-robot formation control
0.412019
Distributed Multi-Robot Formation Splitting and Merging in Dynamic Environments · ICRA 2019
Robotics › Motion planning and robot control
collision avoidance
0.112019
Distributed Multi-Robot Formation Splitting and Merging in Dynamic Environments · ICRA 2019
Knowledge, reasoning and agents › Multi-agent systems › consensus
distributed consensus
0.112019
Distributed Multi-Robot Formation Splitting and Merging in Dynamic Environments · ICRA 2019

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

distributed consensus · 0.4convex region intersection graph · 0.4
YearPublicationVenuePosition
2019 Distributed Multi-Robot Formation Splitting and Merging in Dynamic Environments
abstract
This paper presents a distributed method for splitting and merging of multi-robot formations in dynamic environments with static and moving obstacles. Splitting and merging actions rely on distributed consensus and can be performed to avoid obstacles. Our method accounts for the limited communication range and visibility radius of the robots and relies on the communication of obstacle-free convex regions and the computation of an intersection graph. In addition, our method is able to detect and recover from (permanent and temporary) communication and motion faults. Finally, we demonstrate the applicability and scalability of the proposed method in simulations with up to sixteen quadrotors and real-world experiments with a team of four quadrotors.
Hai Zhu 0002, Jelle Juhl, Laura Ferranti, Javier Alonso-Mora
ICRA2