Development of a Fault-Tolerant Control System for a Swarm of Drones

Tahir, Anam; Böling, Jari M.; Haghbayan, Mohammad-Hashem; Plosila, Juha

doi:10.1109/elmar49956.2020.9219027

Cited by 10 publications

(9 citation statements)

References 16 publications

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“…The distance between the failed leader and followers is calculated using Euclidean distance, and the follower with minimum distance from the faulty leader is selected as a new leader for a swarm. A similar failure recovery strategy based on the shortest path planning/replanning problem is proposed by Tahir et al in [21] for rerouting UAVs, which is the prequel work of this study.…”

Section: Related Workmentioning

confidence: 99%

“…The full failure of an engine of a node in the swarm of UAVs using leader-follower tightly coupled formation is considered in [21]. As a solution, a bottom-up reconfiguration is imposed to bypass the failed node in order to keep the formation intact.…”

Section: B Distance-and Time-optimal Algorithmsmentioning

confidence: 99%

“…As a solution, a bottom-up reconfiguration is imposed to bypass the failed node in order to keep the formation intact. For this study, the proposed method in [21] is extended for the reconfiguration of a multi-drone system after simultaneous failures of multiple nodes. The following two alternative algorithms are used for reconfiguration of the swarms, which are based on a combinatorial search with some application-dependent pruning heuristics.…”

Section: B Distance-and Time-optimal Algorithmsmentioning

confidence: 99%

“…The motion of each drone is controlled using a standard LQR with integral action [21], [31]- [34]. LQR is a method for the design of an optimal state feedback law based on a linear model, in this case Equation (8).…”

Section: A Tracking Control Of Uavsmentioning

confidence: 99%

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Energy-Efficient Post-Failure Reconfiguration of Swarms of Unmanned Aerial Vehicles

et al. 2023

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In this paper, the reconfiguration of swarms of unmanned aerial vehicles after simultaneous failures of multiple nodes is considered. The objectives of the post-failure reconfiguration are to provide collision avoidance and smooth energy-efficient movement. To incorporate such a mechanism, three different failure recovery algorithms are proposed namely thin plate spline, distance-and time-optimal algorithms. These methods are tested on six swarms, with two variations on failing nodes for each swarm. Simulation results of reconfiguration show that the execution of such algorithms maintains the desired formations with respect to avoiding collisions at run-time. Also, the results show the effectiveness concerning the distance travelled, kinetic energy, and energy efficiency. As expected, the distance-optimal algorithm gives the shortest movements, and the time-optimal algorithm gives the most energy-efficient movements. The thin plate spline is also found to be energy-efficient and has less computational cost than the other two proposed methods. Despite the suggested heuristics, these are combinatorial in nature and might be hard to use in practice. Furthermore, the use of the regularization parameter λ in thin plate spline is also investigated, and it is found that too large values on λ can lead to incorrect locations, including multiple nodes on the same location. In fact, it is found that using λ = 0 worked well in all cases.

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Section: Related Workmentioning

confidence: 99%

Section: B Distance-and Time-optimal Algorithmsmentioning

confidence: 99%

Section: B Distance-and Time-optimal Algorithmsmentioning

confidence: 99%

Section: A Tracking Control Of Uavsmentioning

confidence: 99%

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Energy-Efficient Post-Failure Reconfiguration of Swarms of Unmanned Aerial Vehicles

et al. 2023

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“…However, the cumulative error generated by the pseudospectral methods may lead to the divergence of trajectories under open loop control. Therefore, a feedback controller (e.g., an LQR controller which has been widely used in UAV systems [34][35][36] ) is applied in this article to ensure the optimal trajectories being precisely tracked.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning with mid-air collision avoidance for quadrotor unmanned aerial vehicles

Jiang

Damaren

2021

Proceedings of the Institution of Mechanical Engineers, Part G:

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Flight collision between unmanned aerial vehicles (UAVs) in mid-air poses a potential risk to flight safety in low-altitude airspace. This article transforms the problem of collision avoidance between quadrotor UAVs into a trajectory-planning problem using optimal control algorithms, therefore achieving both robustness and efficiency. Specifically, the pseudospectral method is introduced to solve the raised optimal control problem, while the generated optimal trajectory is precisely followed by a feedback controller. It is worth noting that the contributions of this article also include the introduction of the normalized relative coordinate, so that UAVs can obtain collision-free trajectories more conveniently in real time. The collision-free trajectories for a classical scenario of collision avoidance between two UAVs are given in the simulation part by both solving the optimal control problem and querying the prior results. The scalability of the proposed method is also verified in the simulation part by solving a collision avoidance problem among multiple UAVs.

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A multi‐UAV system for coverage path planning applications with in‐flight re‐planning capabilities

Luna,

Molina,

Da‐Silva‐Gomez

et al. 2024

Journal of Field Robotics

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This paper presents the development and implementation of a multiple unmanned aerial vehicle system focused on coverage path planning on multiple separated areas capable of re‐planning the collective mission in case of unexpected events. For this purpose, we present a distributed‐centralized architecture that uses heuristic and computationally efficient methods to perform the planning/re‐planning and decision‐making tasks during the control of the mission execution. We performed a computational evaluation of the algorithms, comparing them with other proposals, together with experiments in simulated and real flights. The results show that the system can distribute tasks equitably among the aircraft in an efficient way, even in the middle of the flight, when facing unexpected events; and show a higher computational efficiency when compared to multiple proposals in the state of the art.

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Development of a Fault-Tolerant Control System for a Swarm of Drones

Cited by 10 publications

References 16 publications

Energy-Efficient Post-Failure Reconfiguration of Swarms of Unmanned Aerial Vehicles

Energy-Efficient Post-Failure Reconfiguration of Swarms of Unmanned Aerial Vehicles

Trajectory planning with mid-air collision avoidance for quadrotor unmanned aerial vehicles

A multi‐UAV system for coverage path planning applications with in‐flight re‐planning capabilities

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