Method of cooperative self-adaptation intelligent planning of complex mixed path of carrying robot

Abstract

The invention discloses a method of cooperative self-adaptation intelligent planning of a complex mixed path of a carrying robot. The method comprises the following steps: Step 1: constructing a three-dimensional coordinate system of a global map; Step 2: dividing the global map according to floor numbers, so as to acquire a two-dimensional map and a distance matrix of each floor; Step 3: acquiring coordinates of a starting point and a termination point of a transportation task in the three-dimensional coordinate system of the global map according to an instruction of the transportation task and planning a path by adopting a Floyd algorithm according to the distance matrix of each floor and distance matrixes of all corridors and rooms in each floor, so as to acquire a transportation planned path; Step 4: controlling the carrying robot to advance according to the planned path, so as to complete the transportation task. According to the method, module division is performed on a multi-floor environment, so that the calculated amount of the algorithm is decreased; the method comprises the interaction of an access control and an elevator and an obstacle avoidance strategy, so that the carrying robot can be configured to execute the transportation task in an intelligent environment conveniently.

Description

technical field [0001] The invention belongs to the path planning problem of a robot, and in particular relates to a collaborative adaptive intelligent planning method for a complex mixed path of a carrying robot. Background technique [0002] With the opening of the industry 4.0 era, artificial intelligence is hot, and robots have begun to enter daily life, laboratories, factories and other fields. Due to the rapid development of science and technology, robots have become more and more widely used, expanding from 95% of industrial applications to more non- Industrial applications play an increasingly important role in society. Moreover, since China promoted the development of the robot industry, it is growing into the world's largest robot market, and the "Chinese era" of robots may be coming soon. How to make robots serve humans more efficiently and intelligently is the focus of everyone's attention. Among them, the path planning and control of transportation robots is th...

AI Technical Summary

Problems solved by technology

This method is one of the most commonly used methods to solve robot path planning problems. Through continuous information exchange between feasible solutions, a better path can be found. It has the advantages of strong robustness and high feasibility, but it is easy to fall into local problems. Optimal solution, large amount of calculation leads to too long calculation time, too slow response is not conducive to the operation of the robot in the real environment, resulting in low efficiency of work

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