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Jan Faigl – One of the best experts on this subject based on the ideXlab platform.

  • MESAS – Aerial Reconnaissance and Ground Robot Terrain Learning in Traversal Cost Assessment
    Modelling and Simulation for Autonomous Systems, 2020
    Co-Authors: Milos Pragr, Petr Vaňa, Jan Faigl

    Abstract:

    In this paper, we report on the developed system for assessment of ground unit terrain traversal cost using Aerial Reconnaissance of the expected mission environment. The system combines an Aerial vehicle with ground robot terrain learning in the traversal cost modeling utilized in the mission planning for ground units. The Aerial vehicle is deployed to capture visual data used to build a terrain model that is then used for the extraction of the terrain features of the expected operational area of the ground units. Based on the previous traversal experience of the ground units in similar environments, the learned model of the traversal cost is employed to predict the traversal cost of the new expected operational area to plan a cost-efficient path to visit the desired locations of interest. The particular modules of the system are demonstrated in an experimental scenario combining the deployment of an unmanned Aerial vehicle with a multi-legged walking robot used for learning the traversal cost model.

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  • Aerial Reconnaissance and ground robot terrain learning in traversal cost assessment
    international conference on Modelling and simulation, 2019
    Co-Authors: Milos Pragr, Petr Vaňa, Jan Faigl

    Abstract:

    In this paper, we report on the developed system for assessment of ground unit terrain traversal cost using Aerial Reconnaissance of the expected mission environment. The system combines an Aerial vehicle with ground robot terrain learning in the traversal cost modeling utilized in the mission planning for ground units. The Aerial vehicle is deployed to capture visual data used to build a terrain model that is then used for the extraction of the terrain features of the expected operational area of the ground units. Based on the previous traversal experience of the ground units in similar environments, the learned model of the traversal cost is employed to predict the traversal cost of the new expected operational area to plan a cost-efficient path to visit the desired locations of interest. The particular modules of the system are demonstrated in an experimental scenario combining the deployment of an unmanned Aerial vehicle with a multi-legged walking robot used for learning the traversal cost model.

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Qu Guo-zhi – One of the best experts on this subject based on the ideXlab platform.

  • Fast mosaic method of Aerial Reconnaissance images using affine transform and cross-correlation
    Journal of Optoelectronics·laser, 2011
    Co-Authors: Qu Guo-zhi

    Abstract:

    A fast image mosaic method is proposed for an Aerial Reconnaissance CCD camera.In this method,parameters of affine transformation were first evaluated by using the work parameters of the camera,which can supply a rough registration area of images.Then,the image cross-correlation was employed to obtain a higher precision in the affine transformation parameters by searching this rough area.Finally,a bilinear interpolation method was used to fuse the overlapping area of images.Experimental results of this method prove that it can reduce the processing time effectively,abate the requirements for image processing hardware,and prevent the wrong matching caused by only using cross-correlation method.Images generated by the method can meet the requirements of camera systems.

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  • Design of super-wide-angle Aerial Reconnaissance CCD camera
    Infrared and Laser Engineering, 2010
    Co-Authors: Qu Guo-zhi

    Abstract:

    A new design scheme of super-wide-angle Aerial Reconnaissance CCD camera is described,which is composed of an optical drum and a reflecting mirror rotation mechanism.The optical drum is installed optically parallel to the aircraft velocity,and the reflecting mirror is positioned inside of the optical drum.Partial images are taken during the optical drum rotation,and image motion caused by the roll and the pitch attitude disturbance were compensated by the optical drum and the mirror rotation mechanism,respectively.Unlike the traditional CCD camera,this camera possesses characteristics of small body size,super-wide-angle and high resolution images with adjustable image overlap rates,and it does not require any other compensation mechanism.Finally,there-channel images taken during flight test are presented to demonstrate the effectiveness of the designed camera.The result shows that the scheme meets Aerial Reconnaissance with wide view field and high resoultion.

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  • Calculating Attitude Disturbance Image Motion of One Aerial Reconnaissance CCD Camera
    Opto-electronic Engineering, 2010
    Co-Authors: Qu Guo-zhi

    Abstract:

    According to the operating principle of one scanning Aerial Reconnaissance CCD camera, an analysis expression of image motion was derived with collinearity equation, which was about attitude disturbance and image obliquity. Combining the working parameters of imaging obliquity and attitude disturbance, a simulation analysis was given, and the results show that image motion is independent on image obliquity and linearizes relationship of attitude disturbance when image obliquity θ0.13 rad. Beyond this range, image motion is nonlinear with image obliquity and attitude disturbance. The whole trends will increase coupling with the increase of the disturbance, which can supply a theory basis for the same species of camera and its image motion compensation devices.

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William B Carlton – One of the best experts on this subject based on the ideXlab platform.

  • reactive tabu search in unmanned Aerial Reconnaissance simulations
    Winter Simulation Conference, 1998
    Co-Authors: Joel L Ryan, Glenn T Bailey, James T Moore, William B Carlton

    Abstract:

    We apply a Reactive Tabu Search (RTS) heuristic within a discrete-event simulation to solve routing problems for unmanned Aerial vehicles (UAVs). Our formulation represents this problem as a multiple traveling salesman problem with time windows (mTSPTW), with the objective of maximizing expected target coverage. Incorporating weather and probability of UAV survival at each target as random inputs, the RTS heuristic in the simulation searches for the best solution in each realization of the problem scenario in order to identify those routes that are robust to variations in weather, threat, or target service times. We present an object-oriented implementation of this approach using CACI’s simulation language MODSIM.

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