Trajectory online optimization for unmanned combat aerial vehicle using combined strategy

Dong, Kangsheng; Huang, Hanqiao; Huang, Changqiang; Zhang, Zhuoran

doi:10.21629/jsee.2017.05.14

Cited by 4 publications

(3 citation statements)

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“…Equation ( 14) is the equation for the repulsion potential used in the equation for the repulsion rate. The repulsive potential equation is partially derived around the 𝑥 and 𝑦 axes shown in (15) and ( 16) [65], [66].…”

Section: Fig 2 No Lateral Slipmentioning

confidence: 99%

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Potential Force Algorithm with Kinematic Control as Path Planning for Disinfection Robot

Suwarno

Oktaviani

Apriani³

et al. 2022

Journal of Robotics and Control

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The disinfection robot is a virus-sterilizing robot that uses a nonholonomic robot model. Route planning algorithms are needed to allow disinfection robots to sterilize rooms in unknown areas and perform the task while navigating using a potential field algorithm. There is a problem applying the algorithm to nonholonomic robots: avoiding obstacles. The proposed route planning algorithm has been transformed into a potential force used to plan the path of disinfection robots in static and dynamic environments and environments with static obstacles. A potential field algorithm is used. There are some issues when the potential force algorithm is applied to nonholonomic disinfection robots in the area. Like any other robot, it takes a long time to avoid static obstacles. Therefore, this paper proposed a potential force algorithm that allows a robot to move towards a target point while avoiding static obstacles. The algorithm showed that a modified potential field algorithm with potential force could be applied to differential-driven robots for path planning. The disinfection robot could avoid obstacles with a faster response using this algorithm.

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Section: Fig 2 No Lateral Slipmentioning

confidence: 99%

“…[13] How to design a logistics path with four fine parameters of a ring-shaped path was investigated by Upadhyay [14]. A combined strategy for online trajectory optimization of unmanned combat aerial vehicles was investigated by Dong [15]. The evolution method of route planning is Z.…”

Section: Introductionmentioning

confidence: 99%

Potential Force Algorithm with Kinematic Control as Path Planning for Disinfection Robot

Suwarno

Oktaviani

Apriani³

et al. 2022

Journal of Robotics and Control

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show abstract

“…Different from K-means clustering method, the whole population is divided into several subpopulations in Ref. [16]. As there are different forms of position update formulas in differential algorithm (DE), such as DE/rand1, DE/rand/2, DE/best/1 and DE/current-to rand/1, each subpopulation can select a kind of formula to update the solutions, which can make each subpopulation evolve from different directions.…”

Section: Related Workmentioning

confidence: 99%

Swarm-Based 4D Path Planning For Drone Operations in Urban Environments

Low

Pang

et al. 2021

IEEE Trans. Veh. Technol.

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Drones have a wide range of applications in urban environments as they can both enhance people's daily activities and commercial activities through various operations and deployments. With the increasing number of drones, flight safety and efficiency become the main concern, and effective drone operations can make a difference. Accordingly, 4D path planning for drone operations is the focus of this paper, and the swarm-based method is proposed to solve this complicated optimization problem. Under the framework of 'AirMatrix', the problem is solved in two levels, i.e., 3D path planning for a single drone and conflict resolution among drones. In the multipath planning level, multiple alternative flight paths for each drone are generated to increase the acceptance rate of a flight request. The constraints on a single flight path and two different flight paths are considered. The goal is to obtain several different short flight paths as alternatives. A clustering improved ant colony optimization (CIACO) algorithm is employed to solve the multi-path planning problem. The crowding mechanism is used in clustering, and some improvements are made to strengthen the global and local search ability in the early and later phases of iterations. In the task scheduling level, the conflicts between two drones are defined in two circumstances. One is for the time interval of passing the same path point, another one is for the right-angle collision between two drones. A three-layer fitness function is proposed to maximize the number of permitted flights according to the safety requirement, in which the airspace utilization and the operators' requests are both considered. A 'cross-off' strategy is developed to calculate the fitness value, and a 'distributed-centralized' strategy is applied considering the task priorities of drones. A genetic algorithm (GA)-based task scheduling algorithm is also developed according to the characteristic of the established model. Simulation results demonstrate that 4D flight path of each drone can be generated by the proposed swarmed-based algorithms, and safe and efficient drone operations in a specific airspace can be ensured.

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A survey on population-based meta-heuristic algorithms for motion planning of aircraft

2021

Swarm and Evolutionary Computation

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Trajectory online optimization for unmanned combat aerial vehicle using combined strategy

Cited by 4 publications

References 0 publications

Potential Force Algorithm with Kinematic Control as Path Planning for Disinfection Robot

Potential Force Algorithm with Kinematic Control as Path Planning for Disinfection Robot

Swarm-Based 4D Path Planning For Drone Operations in Urban Environments

A survey on population-based meta-heuristic algorithms for motion planning of aircraft

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