Inverse kinematics algorithm of electric intelligent bionic climbing robot

Abstract

The invention discloses an inverse kinematics algorithm of an electric intelligent bionic climbing robot, which comprises the following steps of: constructing a model of the robot, and respectively establishing a base coordinate system and a coordinate system of each joint; using a vector formed by all joint corners of the robot as the position x of the longhorn beetles, constructing a fitness function F (x), and obtaining the fitness value fx of the position x of the longhorn beetles; after iteration of the longhorn beetle algorithm, obtaining the optimal position xbest of the longhorn beetle, namely the optimal value of the rotation angle of each joint of the robot is obtained; according to the improved longicorn beetle algorithm, performing searching based on a variable step size step of negative exponential power attenuation, the variable step size step is gradually classified as a basic resolution step 'along with the increase of iteration times, the position of next iteration of longicorn beetles is updated and referenced to the globally optimal left beetle fitness value and the globally optimal right beetle fitness value, the acceptance probability p is introduced, and a relatively inferior solution is accepted with the proper acceptance probability p. The robot inverse kinematics method based on the improved longhorn beetle algorithm is higher in reliability, higher in precision and higher in convergence speed.

Description

technical field [0001] The invention relates to the technical field of robot kinematics inverse solution, in particular to a kinematics inverse solution algorithm of an electric intelligent bionic climbing robot. Background technique [0002] At present, it has become a hot topic to use industrial robots instead of manual labor to complete dangerous inspection tasks, for example, electric intelligent bionic climbing robots with six degrees of freedom structure. [0003] The kinematic inverse solution of industrial robots refers to the calculation of each joint angle through the given target robot end pose parameters, which has important research significance for the dynamic performance analysis of robot trajectory planning. At present, the kinematic inverse solution method of industrial robots, that is, the solution method of the inverse running equation is mainly geometric method, analytical method and numerical method. For the geometric method, Xu Wenfu et al. proposed an...

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Problems solved by technology

Wang Chen, Xiang Changfeng et al. proposed an improved beetle whisker algorithm with variable step size, which can improve the speed of beetle search optimization to a certain extent, but because the basic resolution of the step size is not set, it will lead to invalid iterations in the later iterations. Happening

Lu Guanghui, Teng Huan, etc. introduced the Monte Carlo rule in the simulated annealing algorithm to the beetle's whisker algorithm, which improved the stability of the algorithm and applied it to the problem of distributed power source location selection and fixed capacity. Efficient, but when dealing with high-dimensional, nonlinear, and strongly coupled problems such as six-degree-of-freedom articulated robots, the solution accuracy is limited

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