Automatic navigation system based on camera detection, control method of system and vertical balance car

Abstract

The invention discloses an automatic navigation system based on camera detection, a control method of the system and a vertical balance car. The system comprises a vertical balance data collection module, a camera data collection module and a signal processing and control module, wherein the vertical balance data collection module and the camera data collection module are connected with the signal processing and control module, the vertical balance data collection data obtains present attitude angle data of the vertical balance car, the camera data collection module collects gray-level image data of a runway, and the signal processing and control module collects, stores and processes the gray-level image data of the runway, the present attitude angle data of the vertical balance car, and present speed and differential speed data of the vertical balance car, and controls the balance of the vertical balance car according to the present attitude angle data of the vertical balance car. Thus, the road condition in front can be effective predicted, prediction can be controlled more effectively, and the control precision is improved.

Description

technical field [0001] The invention relates to an automatic navigation system, especially an automatic navigation system based on camera detection, a control method and an upright balancing vehicle, belonging to the technical fields of information technology, automation technology, automatic navigation technology, self-balancing technology and the like. Background technique [0002] Automatic navigation technology has always been one of the hotspots of people's research. At present, traditional automatic navigation technology systems mostly use 1) GPS system navigation 2) photoelectric sensors 3) electromagnetic sensors; systems using GPS navigation, due to civilian GPS positioning accuracy and data sampling Due to the speed limit, the phenomenon of "drift" often occurs, resulting in control lag, low control accuracy, and poor real-time performance; systems using photoelectric sensors and electromagnetic sensors for navigation have high sampling rates and good measurement ac...

AI Technical Summary

Problems solved by technology

[0002] Automatic navigation technology has always been one of the hotspots of people's research. At present, traditional automatic navigation technology systems mostly use 1) GPS system navigation 2) photoelectric sensors 3) electromagnetic sensors; systems using GPS navigation, due to civilian GPS positioning accuracy and data sampling Due to the speed limit, the phenomenon of "drift" often occurs, resulting in control lag, low control accuracy, and poor real-time performance; systems using photoelectric sensors and electromagnetic sensors for navigation have high sampling rates and good measurement accuracy, but photoelectric sensors Compared with the electromagnetic sensor, it is a "line" and "point" measurement, that is, a "single-dimensional" measurement, which cannot measure the overall characteristics of the road surface, resulting in the system only measuring the current road surface state and it is difficult to obtain the future road surface state

[0003] The traditional self-balancing car uses an 8-bit single-chip microcomputer of 8MHz, which has low calculation accuracy, slow calculation speed, and slow sampling rate.

At the same time, at present, the automatic navigation system is mostly used on four-wheel vehicles. The four-wheel characteristics of four-wheel vehicles determine the characteristics of inflexible movement and inconvenient steering.

[0004] With the development of self-balancing car technology, self-balancing car will play an important role in many occasions, but self-balancing car technology using cameras for automatic navigation is still blank

In addition, the single-axis attitude algorithm used by the traditional self-balancing vehicle is slightly less secure than the three-axis attitude algorithm.

Images