A Space Mapping Based 0–1 Linear Model for Onboard Conflict Resolution of Heterogeneous Unmanned Aerial Vehicles

Yang, Jian; Xu, Xin; Yin, Dong; Ma, Zhiliang

doi:10.1109/tvt.2019.2919737

Cited by 18 publications

(15 citation statements)

References 29 publications

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“…According to the six degree-of-freedom motion equations of UAV [ 23 ], the partial velocities of each member in the swarm system in the three axes in the geographic coordinate system are

, respectively:

where x , y , z are the three-axis coordinates of the UAV, ψ , θ are the track deflection angle and track inclination angle of the UAV, V is the flight speed scalar of the UAV, and the two angular speeds

of the UAV are expressed by the following formula:

where κ ψ and κ θ are the acceleration term coefficients of angular velocity.…”

Section: Basic Flight Behavior Rules Of Swarmmentioning

confidence: 99%

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Anticollision Decision and Control of UAV Swarm Based on Intelligent Cognitive Game

Huan

Han

2022

Computational Intelligence and Neuroscience

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UAV swarm anticollision system is very important to improve the flight safety of the whole swarm formation, while the existing system design methods are still insufficient in realizing autonomous and cooperative anticollision. Based on the cognitive game theory, an intelligent decision-making and control method for UAV swarm anticollision is designed. Firstly, by using the idea of swarm intelligence, basic flight behaviors of UAV swarm are defined as five basic flight rules, such as cohesion, following, self-guidance, dispersion, and alliance. Further, the cognitive security domain of UAV swarm is constructed by setting the overall anticollision rules of the swarm and the anticollision rules of individual members. On this basis, the anticollision problem of UAV swarm is transformed into a game problem involving two parties, and the solution method of decision and control strategy set is proposed. Finally, the stability of anticollision decision and control method is proved through eigenvalue theory. The simulation results show that the method proposed in this paper can effectively realize the autonomous cooperative anticollision of UAV swarm and also has good algorithm real-time solution ability while ensuring flight safety.

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“…According to the six degree-of-freedom motion equations of UAV [ 23 ], the partial velocities of each member in the swarm system in the three axes in the geographic coordinate system are

, respectively:

of the UAV are expressed by the following formula:

where κ ψ and κ θ are the acceleration term coefficients of angular velocity.…”

Section: Basic Flight Behavior Rules Of Swarmmentioning

confidence: 99%

“…According to the six degree-of-freedom motion equations of UAV [23], the partial velocities of each member in the swarm system in the three axes in the geographic coordinate system are _…”

Section: Basic Flight Rules For Internal Members Of the Swarmmentioning

confidence: 99%

Anticollision Decision and Control of UAV Swarm Based on Intelligent Cognitive Game

Huan

Han

2022

Computational Intelligence and Neuroscience

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“…Equation (27) map angles to sine values. The feasible regions are therefore described by linear constraints in sine value space 31 :…”

Section: The Space Mapping Based Conflict Resolution Algorithmsmentioning

confidence: 99%

“…Nevertheless, the calculating time spent by the proposed stochastic parallel gradient descent (SPGD) method varies over time as the search process is directed by stochastic gradient. Furthermore, Yang et al 30,31 propose the space mapping based conflict resolution method. These two methods could greatly improve the computation efficiency.…”

Section: Introductionmentioning

confidence: 99%

Online cooperative airspace conflict resolution of unmanned aerial vehicles by space mapping based iterative search method

Zhao

Wang

Yang

et al. 2022

Advances in Mechanical Engineering

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This paper presents an investigation into the locally centralized conflict resolution problem of unmanned aerial vehicles (UAVs), in which the headings are adjustable variables. Firstly, the geometric characteristics of the conflict resolution problem in two-dimensional space are studied, and the problem is reduced into a nonlinear programing model. Secondly, the nonlinear safe separation constraint is transferred into linear style in the sine value space using the space mapping method. The feasible region of two conflict-related UAVs is transformed into a half-space in the sine value space. The minimum adjustment vector and the maximum adjustable vector are obtained in this space. Thirdly, to search for the local optimal conflict-free solution, a two-layered optimization method is given. In the first layer, feasible conflict-free solutions are obtained by iterative search in virtue of the minimum adjustment vector and the maximum adjustable vector. In the second layer, the local optimal solution is generated using the sequential quadratic programing (SQP) method. The effectiveness of the proposed method is verified by numerical simulations. Compared with the existing geometric guidance theory based methods, the proposed method could effectively generate conflict-free solutions that lead to fewer detours, through which UAVs could coordinate online in highly crowded airspace.

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“…Although several problems can be modeled as QUBO (e.g., [9]- [11]), most optimization problems of practical interest contain both discrete and continuous variables. For instance, mixed-integer linear programming (MILP) problems are commonly used in diverse application areas, such as logistics [12], the coordination of unmanned aerial vehicles [13] and power systems [14].…”

Section: A Decomposition-based Hqc Algorithmsmentioning

confidence: 99%

Hybrid Quantum-Classical Multi-cut Benders Approach with a Power System Application

Paterakis¹

2021

Preprint

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Leveraging the current generation of quantum devices to solve optimization problems of practical interest necessitates the development of hybrid quantum-classical (HQC) solution approaches. In this paper, a multi-cut Benders decomposition (BD) approach that exploits multiple feasible solutions of the master problem (MP) to generate multiple valid cuts is adapted, so as to be used as an HQC solver for general mixed-integer linear programming (MILP) problems. The use of different cut selection criteria and strategies to manage the size of the MP by eliciting a subset of cuts to be added in each iteration of the BD scheme using quantum computing is discussed. The HQC optimization algorithm is applied to the Unit Commitment (UC) problem. UC is a prototypical use case of optimization applied to electrical power systems, a critical sector that may benefit from advances in quantum computing. The validity and computational viability of the proposed approach are demonstrated using the D-Wave Advantage 4.1 quantum annealer.

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A Space Mapping Based 0–1 Linear Model for Onboard Conflict Resolution of Heterogeneous Unmanned Aerial Vehicles

Cited by 18 publications

References 29 publications

Anticollision Decision and Control of UAV Swarm Based on Intelligent Cognitive Game

Anticollision Decision and Control of UAV Swarm Based on Intelligent Cognitive Game

Online cooperative airspace conflict resolution of unmanned aerial vehicles by space mapping based iterative search method

Hybrid Quantum-Classical Multi-cut Benders Approach with a Power System Application

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