Indoor navigation method based on connection of multiple 3D (three dimensional)-structure optical cameras

Abstract

The invention discloses an indoor navigation method based on connection of multiple 3D (three dimensional)-structure optical cameras. The indoor navigation method comprises the following steps: expressing a map by using a grid map manner, setting an initial map as null, setting an initial pose of a robot as an origin of a global coordinate system, calculating robot pose prediction quantity according to odometer data through a robot motion model in a process of building the map, simultaneously extracting observation quantity from continuously-updated sensor data by using a feature extraction technology, and calculating the robot pose prediction quantity and a visual global map through a designed observation model to obtain the observation prediction quantity. According to the indoor navigation method based on the connection of the multiple 3D-structure optical cameras, a method for simulating a laser radar by connecting the multiple 3D-structure optical cameras is adopted; the pose estimation is carried out by multiple filtering algorithms based on probability; the robot is positioned and navigated; the data is collected by the 3D-structure optical cameras, so that the method is difficultly influenced by the environment; the method is low in data error, has the advantage of low cost and can make up the shortcomings of the laser radar.

Description

technical field [0001] The invention relates to a navigation method, in particular to an indoor navigation method based on splicing of multiple 3D structured light cameras. Background technique [0002] As the first step of robot intelligence, real-time positioning and navigation technology is constantly attracting attention in the industry. Real-time positioning and navigation means that the robot creates a map in a completely unknown environment under the condition of uncertain position, and uses the map to carry out A technology of autonomous positioning and navigation. In this process, the robot generally determines its own position information through pose estimation and ranging units. Common ranging units include laser ranging, ultrasonic sensors, and image ranging. [0003] Common ranging units include laser ranging, ultrasonic sensors, and image ranging. Laser ranging is to use laser to accurately measure the distance of the target; the ultrasonic sensor adopts the...

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Problems solved by technology

[0004] The accuracy of laser ranging is low and the cost is high; the applicable frequency range and sensitivity of ultrasonic sensor ranging are too small

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