Robot trajectory planning optimal control method based on obstacle size homotopy strategy

Abstract

The invention discloses a robot trajectory planning optimal control method based on an obstacle size homotopy strategy. The robot trajectory planning optimal control method based on the obstacle sizehomotopy strategy comprises the following steps that firstly, a motion equation and constraint conditions are established according to the structural characteristics of a robot, and a feature circle is used for describing the contour of the robot; secondly, according to obstacle information in the working environment, a feature circle is used for describing obstacles, a safety distance is set, andobstacle avoidance conditions in the working process are established; thirdly, initial and terminal boundary conditions corresponding to a robot trajectory planning problem are determined; fourth, the trajectory planning problem is converted to a optimal control problem with minimized energy consumption; and finally, the constructed optimal control problem is converted to a series of sub-problems, the size of one obstacle in each sub-problem continues to increase compared to the previous sub-problem, and the solution of the current sub-problem is used as the initial guess of the next sub-problem. According to the robot trajectory planning optimal control method based on the obstacle size homotopy strategy, the obstacle size homotopy strategy is used to achieve the efficient and stable solution of the robot point-to-point trajectory planning problem in the complex working environment, and the great significance is achieved for trajectory planning problem faced in the actual work of therobot.

Description

technical field [0001] The invention belongs to the field of robot trajectory planning, and relates to an optimal control method for robot trajectory planning based on obstacle size homotopy strategy. Background technique [0002] Commonly used robot trajectory planning methods include graph theory method, artificial potential field method, search method, rapid expansion random tree method, optimal control method, etc. Compared with the other types of methods mentioned, the optimal control method makes the planned trajectory naturally feasible because it is based on the kinematics (or dynamics) equations of the robot. In addition, the optimal control method has a simple mathematical structure, and various constraints such as control saturation and obstacle avoidance can be considered under a unified framework. There may be many obstacles in the actual working environment of the robot. Using the optimal control method to solve the optimization problem will lead to a highly n...

AI Technical Summary

Problems solved by technology

There may be many obstacles in the actual working environment of the robot. Using the optimal control method to solve the optimization problem will lead to a highly nonlinear optimization problem, making the robustness and efficiency of the solution process heavily dependent on the quality of the initial guess.

Since the robot must be in a delicate waiting state before the trajectory planning is completed, if the solution efficiency is slow or fails, it will affect the progress of the entire job task

This objective fact limits the application of the optimal control method in the actual robot trajectory planning problem

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