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
A general method of controller design is developed for the purpose offormation keeping and reconfiguration of nonlinear systems with multiple subsystems, such as theformation of multiple aircraft, ground vehicles, or ...A general method of controller design is developed for the purpose offormation keeping and reconfiguration of nonlinear systems with multiple subsystems, such as theformation of multiple aircraft, ground vehicles, or robot arms. The model consists of multiplenonlinear systems. Controllers are designed to keep the subsystems in a required formation and tocoordinate the subsystems in the presence of environmental changes. A step-by-step algorithm ofcontroller design is developed. Sufficient conditions for the stability of formation tracking areproved. Simulations and experiments are conducted to demonstrate some useful coordination strategiessuch as movement with a leader, simultaneous movement, series connection of formations, andhuman-machine interaction.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A general method of controller design is developed for the purpose offormation keeping and reconfiguration of nonlinear systems with multiple subsystems, such as theformation of multiple aircraft, ground vehicles, or robot arms. The model consists of multiplenonlinear systems. Controllers are designed to keep the subsystems in a required formation and tocoordinate the subsystems in the presence of environmental changes. A step-by-step algorithm ofcontroller design is developed. Sufficient conditions for the stability of formation tracking areproved. Simulations and experiments are conducted to demonstrate some useful coordination strategiessuch as movement with a leader, simultaneous movement, series connection of formations, andhuman-machine interaction.
