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Article
Publication date: 25 January 2008

Haibin Shang, Pingyuan Cui and Enjie Luan

The purpose of this paper is to study the application of the planetary aerogravity‐assist (AGA) technique to the interplanetary transfer mission with low‐thrust engine, and the…

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Abstract

Purpose

The purpose of this paper is to study the application of the planetary aerogravity‐assist (AGA) technique to the interplanetary transfer mission with low‐thrust engine, and the design and optimization approach of low‐thrust AGA trajectory.

Design/methodology/approach

In the research, the transfer trajectory with planetary AGA maneuver is analyzed first, the maximum atmospheric turn angle and the matching condition for AGA trajectory is derived out, which is the significant principle for AGA trajectory design and studies. Then, a design and optimization approach for interplanetary low‐thrust trajectory with AGA maneuver is developed. The complicated design problem is transformed into a parameter optimization problem with multiple nonlinear constraints by using calculus of variations and the matching condition associated with AGA trajectory. Furthermore, since the optimization problem is very sensitive to the launch date and AGA maneuver parameters, three ordinal sub‐problems are reformulated to reduce the sensitivity. Finally, a direct/indirect hybrid approach is utilized to solve these sub‐problems.

Findings

The planetary AGA maneuver is feasible and effective in decreasing the propellant consumption and flight time for interplanetary low‐thrust mission and provides better performance than pure planetary gravity assist. Moreover, the proposed approach is effective to design and optimize the low‐thrust transfer mission with AGA maneuver.

Research limitations/implications

In further research, some simple preliminary design approaches for interplanetary low‐thrust trajectory with AGA maneuver are required to developed, which can provide a good initial conjecture for a hybrid optimization algorithm.

Originality/value

The paper provides the matching condition for interplanetary AGA transfer trajectory by analyzing some characteristics of planetary AGA maneuver, and presents an effective approach to design and optimize interplanetary low‐thrust AGA trajectory.

Details

Aircraft Engineering and Aerospace Technology, vol. 80 no. 1
Type: Research Article
ISSN: 0002-2667

Keywords

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Article
Publication date: 15 March 2013

Zunhui Zhao, Haibin Shang, Pingyuan Cui and Xiangyu Huang

The purpose of this paper is to present a solution space searching method to study the initial design of interplanetary low thrust gravity assist trajectory.

180

Abstract

Purpose

The purpose of this paper is to present a solution space searching method to study the initial design of interplanetary low thrust gravity assist trajectory.

Design/methodology/approach

For reducing the complexity and nonlinearity of the initial design problem, a sixth degree inverse polynomial shape based approach is brought. Then some improvements are provided for solving the parameters in the shape function and a quasi‐lambert solver is brought through the shape based method, the thrust profile can be generated under the given time of flight, boundary states including positions and velocities for low thrust phase. Combining gravity assist model, the problem is summarized and an improved pruning technique is used for searching the feasible solution space for low thrust gravity assist trajectory.

Findings

Using the solution space searching method, the feasible solution region would be generated under the given mission condition. The treatment about gravity assist demonstrates more accurate than previous method. Also another advantage is that the searching method can be used to design different types of mission trajectory, including flyby and rendezvous trajectories.

Practical implications

The method can be used as an efficient approach to search the feasible region for the complex low thrust gravity assist trajectory, and it can provide appropriate initial guesses for the low thrust gravity assist trajectory in mission design phase.

Originality/value

Feasible solution space would be obtained through the searching method. The quasi‐Lambert solver in the paper is found under the shape‐based method and relative improvement, and it shows its availability during the searching process. Through mission trajectory design, the effectiveness of the method is shown.

Details

Aircraft Engineering and Aerospace Technology, vol. 85 no. 2
Type: Research Article
ISSN: 0002-2667

Keywords

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Article
Publication date: 26 August 2024

Hong Long and Haibin Duan

The purpose of this paper is to present and implement a task allocation method based on game theory for reconnaissance mission planning of UAVs and USVs system.

80

Abstract

Purpose

The purpose of this paper is to present and implement a task allocation method based on game theory for reconnaissance mission planning of UAVs and USVs system.

Design/methodology/approach

In this paper, the decision-making framework via game theory of mission planning is constructed. The mission planning of UAVs–USVs is transformed into a potential game optimization problem by introducing a minimum weight vertex cover model. The modified population-based game-theoretic optimizer (MPGTO) is used to improve the efficiency of solving this complex multi-constraint assignment problem.

Findings

Several simulations are carried out to exhibit that the proposed algorithm obtains the superiority on quality and efficiency of mission planning solutions to some existing approaches.

Research limitations/implications

Several simulations are carried out to exhibit that the proposed algorithm obtains the superiority on quality and efficiency of mission planning solutions to some existing approaches.

Practical implications

The proposed framework and algorithm are expected to be applied to complex real scenarios with uncertain targets and heterogeneity.

Originality/value

The decision framework via game theory is proposed for the mission planning problem of UAVs–USVs and a MPGTO with swarm evolution, and the adaptive iteration mechanism is presented for ensuring the efficiency and quality of the solution.

Details

Aircraft Engineering and Aerospace Technology, vol. 96 no. 9
Type: Research Article
ISSN: 1748-8842

Keywords

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Article
Publication date: 2 October 2017

Shanjun Chen and Haibin Duan

The purpose of this paper is to propose an improved optimization method for image matching problem, which is based on multi-scale Gaussian mutation pigeon-inspired optimization…

226

Abstract

Purpose

The purpose of this paper is to propose an improved optimization method for image matching problem, which is based on multi-scale Gaussian mutation pigeon-inspired optimization (MGMPIO) algorithm, with the objective of accomplishing the complicated image matching quickly.

Design/methodology/approach

The hybrid model of multi-scale Gaussian mutation (MGM) mechanism and pigeon-inspired optimization (PIO) algorithm is established for image matching problem. The MGM mechanism is a nonlinear model, which can adjust the position of pigeons by mutation operation. In addition, the variable parameter (VP) mechanism is exploited to adjust the map and compass factor of the original PIO. Low-cost quadrotor, a type of electric multiple rotorcraft, is used as a carrier of binocular camera to obtain the images.

Findings

This work improved the PIO algorithm by modifying the search strategy and adding some limits, so that it can have better performance when applied to the image matching problem. Experimental results show that the proposed method demonstrates satisfying performance in convergence speed, robustness and stability.

Practical implications

The proposed MGMPIO algorithm can be easily applied to solve practical problems and accelerate convergence speed of the original PIO, and thus enhancing the speed of matching process, which will considerably increase the effectiveness of algorithm.

Originality/value

A hybrid model of the MGM mechanism and PIO algorithm is proposed for image matching problem. The VP mechanism and low-cost quadrotor is also utilized in image matching problem.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 6
Type: Research Article
ISSN: 1748-8842

Keywords

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Article
Publication date: 4 June 2024

Dan Zhang, Junji Yuan, Haibin Meng, Wei Wang, Rui He and Sen Li

In the context of fire incidents within buildings, efficient scene perception by firefighting robots is particularly crucial. Although individual sensors can provide specific…

157

Abstract

Purpose

In the context of fire incidents within buildings, efficient scene perception by firefighting robots is particularly crucial. Although individual sensors can provide specific types of data, achieving deep data correlation among multiple sensors poses challenges. To address this issue, this study aims to explore a fusion approach integrating thermal imaging cameras and LiDAR sensors to enhance the perception capabilities of firefighting robots in fire environments.

Design/methodology/approach

Prior to sensor fusion, accurate calibration of the sensors is essential. This paper proposes an extrinsic calibration method based on rigid body transformation. The collected data is optimized using the Ceres optimization algorithm to obtain precise calibration parameters. Building upon this calibration, a sensor fusion method based on coordinate projection transformation is proposed, enabling real-time mapping between images and point clouds. In addition, the effectiveness of the proposed fusion device data collection is validated in experimental smoke-filled fire environments.

Findings

The average reprojection error obtained by the extrinsic calibration method based on rigid body transformation is 1.02 pixels, indicating good accuracy. The fused data combines the advantages of thermal imaging cameras and LiDAR, overcoming the limitations of individual sensors.

Originality/value

This paper introduces an extrinsic calibration method based on rigid body transformation, along with a sensor fusion approach based on coordinate projection transformation. The effectiveness of this fusion strategy is validated in simulated fire environments.

Details

Sensor Review, vol. 44 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 3 January 2017

Jiaqi Jia and Haibin Duan

The purpose of this paper is to propose a novel target automatic recognition method for unmanned aerial vehicle (UAV), which is based on backpropagation – artificial neural…

467

Abstract

Purpose

The purpose of this paper is to propose a novel target automatic recognition method for unmanned aerial vehicle (UAV), which is based on backpropagation – artificial neural network (BP-ANN) algorithm, with the objective of optimizing the structure of backpropagation network, to increase the efficiency and decrease the recognition time. A hardware-in-the-loop system for UAV target automatic recognition is also developed.

Design/methodology/approach

The hybrid model of BP-ANN structure is established for aircraft automatic target recognition. This proposed method identifies controller parameters and reduces the computational complexity. Approaching speed of the network is faster and recognition accuracy is higher. This kind of network combines or better fuses the advantages of backpropagation artificial neural algorithm and Hu moment. with advantages of two networks and improves the speed and accuracy of identification. Finally, a hardware-in-the-loop system for UAV target automatic recognition is also developed.

Findings

The double hidden level backpropagation artificial neural can easily increase the speed of recognition process and get a good performance for recognition accuracy.

Research limitations/implications

The proposed backpropagation artificial neural algorithm can be ANN easily applied to practice and can help the design of the aircraft automatic target recognition system. The standard backpropagation algorithm has some obvious drawbacks, namely, converging slowly and falling into the local minimum point easily. In this paper, an improved algorithm based on the standard backpropagation algorithm is constructed to make the aircraft target recognition more practicable.

Originality/value

A double hidden levels backpropagation artificial neural algorithm is presented for automatic target recognition system of UAV.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

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