A5069377157- Robotic Path Planning Algorithms
- Distributed Control Multi-Agent Systems
- Aerospace Engineering and Control Systems
- UAV Applications and Optimization
- Guidance and Control Systems
- Adaptive Control of Nonlinear Systems
- Transportation and Mobility Innovations
- Underwater Vehicles and Communication Systems
- Neural Networks and Applications
- Vehicle Routing Optimization Methods
- Advanced Chemical Sensor Technologies
- Target Tracking and Data Fusion in Sensor Networks
Université de Technologie de Compiègne
2014-2019
Sorbonne Université
2019
Centre National de la Recherche Scientifique
2019
European Organisation for Rare Diseases
2019
Heuristics and Diagnostics for Complex Systems
2013-2017
Université de Haute-Alsace
2013
The authors interest in this work is to perform a precise real‐time flocking of multiple unmanned aerial vehicles (UAVs). A consensus‐based algorithm that ensures security distance between UAVs proposed. By using Lyapunov theoretical analysis, the propose ultimate boundedness multiple‐UAV system solutions. Moreover, enhanced by distributed integral control renders inter‐distances more precise. Finally, experimental results are provided prove and show efficiency these algorithms.
In this paper, we address the control problem of multiple Unmanned Aerial Vehicles (UAVs) flocking by using a behavior-based strategy. We conceive behavior intending to design towards successful achievement task without fragmentation. Moreover, through its implemention in UAVs, no rendezvous point is needed perform flocking. law, which independent number UAVs flock. use LQR method develop our Our proposed strategy deals with from measurement-mapping perspective. Simulation results show two...
The subject of this paper is a real-time flocking control multiple quadrotors in the context system systems. We believe that most challenging aspect multiple-quadrotor interaction between through sensing and preserving safe interdistances. final objective collision-free flock while navigating to predefined destination. For purpose, we develop laws are based on consensus theory introduced by Olfati-Saber [1]. Our designed order be compatible with experimental implementation nonlinear model...