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Xintong Du

dblp:206/6328 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
0009-0000-6592-793XORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 1 first-authorSystems, architecture and hardware · 2 · 1 first-author

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
2 papers
Motion planning and robot control · 50% Legged, aerial and field robots · 33% Multi-agent systems · 17%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
aerial robots
0.412019
The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education · ICRA 2019
Robotics › Motion planning and robot control › robot control
flight control
0.412019
The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education · ICRA 2019
Robotics › Legged, aerial and field robots › aerial robots › UAV swarm
quadrotor swarm
0.412019
Fast and In Sync: Periodic Swarm Patterns for Quadrotors · ICRA 2019
Knowledge, reasoning and agents › Multi-agent systems › swarm robotics
swarm control
0.412019
Fast and In Sync: Periodic Swarm Patterns for Quadrotors · ICRA 2019
Robotics › Motion planning and robot control
trajectory planning
0.412019
Fast and In Sync: Periodic Swarm Patterns for Quadrotors · ICRA 2019
Robotics › Motion planning and robot control › robot control
trajectory tracking
0.412019
The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education · ICRA 2019
Computing education
robotics education
0.112019
The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education · ICRA 2019

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

state estimation · 0.8aerodynamic characterization · 0.8trajectory generation · 0.4synchronization · 0.4goal assignment · 0.4
YearPublicationVenuePosition
2019 Fast and In Sync: Periodic Swarm Patterns for Quadrotors
abstract
This paper aims to design quadrotor swarm performances, where the swarm acts as an integrated, coordinated unit embodying moving and deforming objects. We divide the task of creating a choreography into three basic steps: designing swarm motion primitives, transitioning between those movements, and synchronizing the motion of the drones. The result is a flexible framework for designing choreographies comprised of a wide variety of motions. The motion primitives can be intuitively designed using a few parameters, providing a rich library for choreography design. Moreover, we combine and adapt existing goal assignment and trajectory generation algorithms to maximize the smoothness of the transitions between motion primitives. Finally, we propose a correction algorithm to compensate for motion delays and synchronize the motion of the drones to a desired periodic motion pattern. The proposed methodology was validated experimentally by generating and executing choreographies on a swarm of 25 quadrotors.
Xintong Du, Carlos E. Luis, Marijan Vukosavljev, Angela P. Schoellig
ICRA1
2019 The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education
abstract
In this paper, we introduce the Phoenix drone: the first completely open-source tail-sitter micro aerial vehicle (MAV) platform. The vehicle has a highly versatile, dual-rotor design and is engineered to be low-cost and easily extensible/modifiable. Our open-source release includes all of the design documents, software resources, and simulation tools needed to build and fly a high-performance tail-sitter for research and educational purposes.The drone has been developed for precision flight with a high degree of control authority. Our design methodology included extensive testing and characterization of the aerodynamic properties of the vehicle. The platform incorporates many off-the-shelf components and 3D-printed parts, in order to keep the cost down. Nonetheless, the paper includes results from flight trials which demonstrate that the vehicle is capable of very stable hovering and accurate trajectory tracking.Our hope is that the open-source Phoenix reference design will be useful to both researchers and educators. In particular, the details in this paper and the available open-source materials should enable learners to gain an understanding of aerodynamics, flight control, state estimation, software design, and simulation, while experimenting with a unique aerial robot.
Xintong Du, Rikky R. P. R. Duivenvoorden, Jonathan Kelly
ICRA2