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Junya Yamauchi

dblp:195/6097 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0002-5827-486XORCID · conflict

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2Applied, interdisciplinary, general and emerging computing · 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
3 papers
Motion planning and robot control · 51% Legged, aerial and field robots · 33% Multi-agent systems · 16%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
multi-robot control
0.822020
Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions · ICRA 2020
Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions · ICRA 2019
Robotics › Motion planning and robot control › mobile robot control
visual coverage control
0.822020
Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions · ICRA 2020
Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions · ICRA 2019
Robotics › Legged, aerial and field robots
aerial robots
0.812024
Distributed Coverage Hole Prevention for Visual Environmental Monitoring With Quadcopters Via Nonsmooth Control Barrier Functions · IEEE Trans. Robotics 2024
Knowledge, reasoning and agents › Multi-agent systems › multi-robot coordination
multi-robot coverage control
0.812024
Distributed Coverage Hole Prevention for Visual Environmental Monitoring With Quadcopters Via Nonsmooth Control Barrier Functions · IEEE Trans. Robotics 2024
Robotics › Legged, aerial and field robots › aerial robot control › UAV control
quadrotor control
0.812024
Distributed Coverage Hole Prevention for Visual Environmental Monitoring With Quadcopters Via Nonsmooth Control Barrier Functions · IEEE Trans. Robotics 2024
Robotics › Motion planning and robot control › robot control › safe control
control barrier functions
0.532024
Distributed Coverage Hole Prevention for Visual Environmental Monitoring With Quadcopters Via Nonsmooth Control Barrier Functions · IEEE Trans. Robotics 2024
Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions · ICRA 2020
Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions · ICRA 2019
Robotics › Motion planning and robot control
robot control
0.222020
Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions · ICRA 2020
Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions · ICRA 2019

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

power diagram · 0.8nonsmooth control barrier functions · 0.8distributed algorithm · 0.8nonsmooth barrier functions · 0.4hybrid systems · 0.4distributed control law · 0.4control barrier functions · 0.4
YearPublicationVenuePosition
2024 Distributed Coverage Hole Prevention for Visual Environmental Monitoring With Quadcopters Via Nonsmooth Control Barrier Functions
abstract
This paper proposes a distributed coverage control strategy for quadcopters equipped with downward-facing cameras that prevents the appearance of unmonitored areas in between the quadcopters' fields of view (FOVs). We derive a necessary and sufficient condition for eliminating any unsurveilled area that may arise in between the FOVs among a trio of quadcopters by utilizing a power diagram, i.e. a weighted Voronoi diagram defined by radii of FOVs. Because this condition can be described as logically combined constraints, we leverage nonsmooth control barrier functions (NCBFs) to prevent the appearance of unmonitored areas among a team's FOV. We then investigate the symmetric properties of the proposed NCBFs to develop a distributed algorithm. The proposed algorithm can support the switching of the NCBFs caused by changes of the quadcopters composing trios. The existence of the control input satisfying NCBF conditions is analyzed by employing the characteristics of the power diagram. The proposed framework is synthesized with a coverage control law that maximizes the monitoring quality while reducing overlaps of FOVs. The proposed method is demonstrated in simulation and experiment.
Riku Funada, Maria Santos 0003, Ryuichi Maniwa, Junya Yamauchi, Masayuki Fujita, Mitsuji Sampei, Magnus Egerstedt
IEEE Trans. Robotics4
2020 Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions
abstract
This paper presents a coverage control algorithm for teams of quadcopters with downward facing visual sensors that prevents the appearance of coverage holes in-between the monitored areas while maximizing the coverage quality as much as possible. We derive necessary and sufficient conditions for preventing the appearance of holes in-between the fields of views among trios of robots. Because this condition can be expressed as logically combined constraints, control nonsmooth barrier functions are implemented to enforce it. An algorithm which extends control nonsmooth barrier functions to hybrid systems is implemented to manage the switching among barrier functions caused by the changes of the robots composing trio. The performance and validity of the proposed algorithm are evaluated in simulation as well as on a team of quadcopters.
Riku Funada, Maria Santos 0003, Takuma Gencho, Junya Yamauchi, Masayuki Fujita, Magnus Egerstedt
ICRA4
2019 Visual Coverage Control for Teams of Quadcopters via Control Barrier Functions
abstract
This paper presents a coverage control strategy for teams of quadcopters that ensures that no area is left unsurveyed in between the fields of view of the visual sensors mounted on the quadcopters. We present a locational cost that quantifies the team's coverage performance according to the sensors' performance function. Moreover, the cost function penalizes overlaps between the fields of view of the different sensors, with the objective of increasing the area covered by the team. A distributed control law is derived for the quadcopters so that they adjust their position and zoom according to the direction of ascent of the cost. Control barrier functions are implemented to ensure that, while executing the gradient ascent control law, no holes appear in between the fields of view of neighboring robots. The performance of the algorithm is evaluated in simulated experiments.
Riku Funada, Maria Santos 0003, Junya Yamauchi, Takeshi Hatanaka, Masayuki Fujita, Magnus Egerstedt
ICRA3