3,170 research outputs found
Decentralized Hybrid Formation Control of Unmanned Aerial Vehicles
This paper presents a decentralized hybrid supervisory control approach for a
team of unmanned helicopters that are involved in a leader-follower formation
mission. Using a polar partitioning technique, the motion dynamics of the
follower helicopters are abstracted to finite state machines. Then, a discrete
supervisor is designed in a modular way for different components of the
formation mission including reaching the formation, keeping the formation, and
collision avoidance. Furthermore, a formal technique is developed to design the
local supervisors decentralizedly, so that the team of helicopters as whole,
can cooperatively accomplish a collision-free formation task
Beyond swarm intelligence: The Ultraswarm
This paper explores the idea that it may be possible to
combine two ideas – UAV flocking, and wireless cluster
computing – in a single system, the UltraSwarm. The
possible advantages of such a system are considered, and
solutions to some of the technical problems are identified.
Initial work on constructing such a system based around
miniature electric helicopters is described
UltraSwarm: A Further Step Towards a Flock of Miniature Helicopters
We describe further progress towards the development of a
MAV (micro aerial vehicle) designed as an enabling tool to investigate aerial flocking. Our research focuses on the use of low cost off the shelf vehicles and sensors to enable fast prototyping and to reduce development costs. Details on the design of the embedded electronics and the
modification of the chosen toy helicopter are presented, and the technique used for state estimation is described. The fusion of inertial data through an unscented Kalman filter is used to estimate the helicopter’s state, and this forms the main input to the control system. Since no detailed dynamic model of the helicopter in use is available, a method is proposed for automated system identification, and for subsequent controller design based on artificial evolution. Preliminary results obtained with a dynamic simulator of a helicopter are reported, along with some encouraging results for tackling the problem of flocking
Visual servoing of an autonomous helicopter in urban areas using feature tracking
We present the design and implementation of a vision-based feature tracking system for an autonomous helicopter. Visual sensing is used for estimating the position and velocity of features in the image plane (urban features like windows) in order to generate velocity references for the flight control. These visual-based references are then combined with GPS-positioning references to navigate towards these features and then track them. We present results from experimental flight trials, performed in two UAV systems and under different conditions that show the feasibility and robustness of our approach
A matlab-based low-cost autopilot for autonomous helicopter development
The challenges associated with the software and hardware integration activities in development of flight autopilot
system for autonomous helicopter have called for a change of
tactics. The resulting effect is for example, a long time delay in autopilot system design, testing and deployment coupled with the fact that several other autonomous helicopter development tasks depend largely on availability of the autopilot system. Though, the use of off-the-shelf autopilot for a flight control system may ease these challenges, they are generally characterized with limited functionalities, and restrict the user’s design authority. As alternative approach, this paper presents the development of a MATLAB-based autopilot system for autonomous helicopter
development. This approach provides an integrated design
environment for rapid-prototyping of a low-cost autopilot system. The results of real-time application of the autopilot for flight data logging are presented. The performance shows the effectiveness of the developed autopilot system in small scale autonomous helicopter design and implementation. This is hope to reduce the design cycle time involves in the deployment of small scale autonomous helicopter in various civil low-cost, small payload applications
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