In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields...In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields (ACF) based method has been proposed recently. This paper deals with the reachability problem of the ACF, that is, how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima. Some sufficient conditions for these purposes are developed theoretically. Theoretical analyses show that, the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles, and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF. Comparisons between the ACF and APF, and simulations are provided to illustrate the advantages of the ACF.展开更多
This paper deals with extensions of higher-order optimality conditions for scalar optimization to multiobjective optimization.A type of directional derivatives for a multiobjective function is proposed,and with this n...This paper deals with extensions of higher-order optimality conditions for scalar optimization to multiobjective optimization.A type of directional derivatives for a multiobjective function is proposed,and with this notion characterizations of strict local minima of order k for a multiobjective optimization problem with a nonempty set constraint are established,generalizing the corresponding scalar case obtained by Studniarski[3].Also necessary not sufficient and sufficient not necessary optimality conditions for this minima are derived based on our directional derivatives,which are generalizations of some existing scalar results and equivalent to some existing multiobjective ones.Many examples are given to illustrate them there.展开更多
Stone Pine(Pinus pinea L.)is currently the pine species with the highest commercial value with edible seeds.In this respect,this study introduces a new methodology for extracting Stone Pine trees from Digital Surface ...Stone Pine(Pinus pinea L.)is currently the pine species with the highest commercial value with edible seeds.In this respect,this study introduces a new methodology for extracting Stone Pine trees from Digital Surface Models(DSMs)generated through an Unmanned Aerial Vehicle(UAV)mission.We developed a novel enhanced probability map of local maxima that facilitates the computation of the orientation symmetry by means of new probabilistic local minima information.Four test sites are used to evaluate our automated framework within one of the most important Stone Pine forest areas in Antalya,Turkey.A Hand-held Mobile Laser Scanner(HMLS)was utilized to collect the reference point cloud dataset.Our findings confirm that the proposed methodology,which uses a single DSM as an input,secures overall pixel-based and object-based F1-scores of 88.3%and 97.7%,respectively.The overall median Euclidean distance revealed between the automatically extracted stem locations and the manually extracted ones is computed to be 36 cm(less than 4 pixels),demonstrating the effectiveness and robustness of the proposed methodology.Finally,the comparison with the state-of-the-art reveals that the outcomes of the proposed methodology outperform the results of six previous studies in this context.展开更多
This article proposes a novel fuzzy virtual force （FVF） method for unmanned aerial vehicle （UAV） path planning in compli-cated environment. An integrated mathematical model of UAV path planning based on virtual fo...This article proposes a novel fuzzy virtual force （FVF） method for unmanned aerial vehicle （UAV） path planning in compli-cated environment. An integrated mathematical model of UAV path planning based on virtual force （VF） is constructed and the corresponding optimal solving method under the given indicators is presented. Specifically,a fixed step method is developed to reduce computational cost and the reachable condition of path planning is proved. The Bayesian belief network and fuzzy logic reasoning theories are applied to setting the path planning parameters adaptively,which can reflect the battlefield situation dy-namically and precisely. A new way of combining threats is proposed to solve the local minima problem completely. Simulation results prove the feasibility and usefulness of using FVF for UAV path planning. Performance comparisons between the FVF method and the A＊ search algorithm demonstrate that the proposed approach is fast enough to meet the real-time requirements of the online path planning problems.展开更多
基金This paper was partly supported by the National Natural Science Foundation (No.60131160741,60334010) of China.
文摘In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields (ACF) based method has been proposed recently. This paper deals with the reachability problem of the ACF, that is, how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima. Some sufficient conditions for these purposes are developed theoretically. Theoretical analyses show that, the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles, and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF. Comparisons between the ACF and APF, and simulations are provided to illustrate the advantages of the ACF.
文摘This paper deals with extensions of higher-order optimality conditions for scalar optimization to multiobjective optimization.A type of directional derivatives for a multiobjective function is proposed,and with this notion characterizations of strict local minima of order k for a multiobjective optimization problem with a nonempty set constraint are established,generalizing the corresponding scalar case obtained by Studniarski[3].Also necessary not sufficient and sufficient not necessary optimality conditions for this minima are derived based on our directional derivatives,which are generalizations of some existing scalar results and equivalent to some existing multiobjective ones.Many examples are given to illustrate them there.
基金supported by the Projects of Scientific Investigation(BAP)of Ankara Haci Bayram Veli University[Grant No.01/2019-32].
文摘Stone Pine(Pinus pinea L.)is currently the pine species with the highest commercial value with edible seeds.In this respect,this study introduces a new methodology for extracting Stone Pine trees from Digital Surface Models(DSMs)generated through an Unmanned Aerial Vehicle(UAV)mission.We developed a novel enhanced probability map of local maxima that facilitates the computation of the orientation symmetry by means of new probabilistic local minima information.Four test sites are used to evaluate our automated framework within one of the most important Stone Pine forest areas in Antalya,Turkey.A Hand-held Mobile Laser Scanner(HMLS)was utilized to collect the reference point cloud dataset.Our findings confirm that the proposed methodology,which uses a single DSM as an input,secures overall pixel-based and object-based F1-scores of 88.3%and 97.7%,respectively.The overall median Euclidean distance revealed between the automatically extracted stem locations and the manually extracted ones is computed to be 36 cm(less than 4 pixels),demonstrating the effectiveness and robustness of the proposed methodology.Finally,the comparison with the state-of-the-art reveals that the outcomes of the proposed methodology outperform the results of six previous studies in this context.
基金National Natural Science Foundation of China (60975073)Aeronautical Science Foundation of China (2008ZC13011)+1 种基金Research Foundation for Doctoral Program of Higher Education of China (20091102110006)Fundamental Research Funds for the Central Universities
文摘This article proposes a novel fuzzy virtual force （FVF） method for unmanned aerial vehicle （UAV） path planning in compli-cated environment. An integrated mathematical model of UAV path planning based on virtual force （VF） is constructed and the corresponding optimal solving method under the given indicators is presented. Specifically,a fixed step method is developed to reduce computational cost and the reachable condition of path planning is proved. The Bayesian belief network and fuzzy logic reasoning theories are applied to setting the path planning parameters adaptively,which can reflect the battlefield situation dy-namically and precisely. A new way of combining threats is proposed to solve the local minima problem completely. Simulation results prove the feasibility and usefulness of using FVF for UAV path planning. Performance comparisons between the FVF method and the A＊ search algorithm demonstrate that the proposed approach is fast enough to meet the real-time requirements of the online path planning problems.
