Mobile robot path planning method based on deep learning

Abstract

The invention provides a mobile robot path planning method based on deep learning. A movement timestamp of a first to-be-operated point is calculated according to an expected speed through a master controller, and a driver is controlled to drive a motor shaft to act through a controller if the movement timestamp is greater than a first specific time value and smaller than a second specific time value; if the movement timestamp is less than the first specific time value, the driver is controlled to maintain the original working state through the controller; if the movement timestamp is greater than the second specific time value, the driver is controlled to interpolate N second to-be-operated points behind the first to-be-operated point to serve as the first to-be-operated point in the next path planning process through the controller, comparison is carried out on the movement timestamp and the specific time, interpolating a new operation point or working or maintaining the original state is selected to re-correct the path curve to the next to-be-operated point, the steps are simple, calculation is convenient, position closed-loop curve calculation can be carried out without periodically sending test information and receiving feedback information, the communication time is saved, and a more reasonable route is corrected in real time.

Description

technical field [0001] The invention relates to the technical field of industrial robots, in particular to a method for path planning of a mobile robot based on deep learning. Background technique [0002] At present, automation technology is developing rapidly. The robot system in this field is an automatic operation system composed of robots, peripheral equipment and tools. Robots, especially industrial robots, are generally multi-axis mechanical arms, and their axes are mainly composed of gearboxes and servo motors. It also includes many independently moving and rotating parts, and the robot control system is mainly composed of a main controller and a servo drive controller. [0003] At present, leading robot control systems at home and abroad, especially industrial robot control systems, are developing in the direction of further improvement in control accuracy, better security, and more convenient input and output. In order to achieve the purpose of the robot to comple...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the existing problems such as complex realization of the re-planning operation point technology, too much calculation, and affecting work efficiency, the present invention provides a mobile robot path planning method and system based on deep learning to solve the existing re-planning operation point technology. Complicated, too much calculation, long communication time, and affect work efficiency and other issues

Images