Mapping method based on multi-sensor mobile robot

Abstract

The invention provides a mapping method based on a multi-sensor mobile robot. The mapping method comprises the following steps of installing multiple different sensors for a robot, and obtaining measurement data of the corresponding sensors; performing operation on inertial measurement unit data and encoder data to obtain robot attitude information and a walking route; converting binocular cameradata, laser radar data and ultrasonic data into a numerical value pair format formed by angles and distances, and respectively constructing two-dimensional point cloud charts of the environment; presetting a threshold value for the sensors, removing distorted point cloud information and redundant point cloud information, and completing optimization of a point cloud image; and converting the optimized point cloud image into a grid map, and completing the creation of the map. According to the method, multiple different sensors are combined, the limitation of a single sensor is made up, map construction and map optimization of the robot are carried out separately, the operand in the map construction process is reduced, and the map construction accuracy and the map construction quality are further improved.

Description

technical field [0001] The invention relates to the field of mapping, in particular to a mapping method based on a multi-sensor mobile robot. Background technique [0002] At present, the movement of robots mostly relies on manual path planning, and the autonomous navigation ability of robots relies on real-time positioning and mapping technology. In addition to being applied in the field of robotics, in order to realize the autonomous navigation and positioning of smart mobile devices, it is necessary to realize the environmental mapping of the environment in which smart mobile devices are located. [0003] Most existing products usually implement environment mapping in two ways. The first is to directly use two-dimensional ranging sensors for environmental mapping, but this cannot obtain three-dimensional information of the environment; the second is to use three-dimensional lidar or image However, this method generally extracts three-dimensional (or image) features first...

AI Technical Summary

Problems solved by technology

[0003] Most existing products usually implement environment mapping in two ways. The first is to directly use two-dimensional ranging sensors for environmental mapping, but this cannot obtain three-dimensional information of the environment; the second is to use three-dimensional lidar or image However, this method generally extracts three-dimensional (or image) features first, performs feature matching, and then estimates the transformation matrix. The amount of calculation is huge, and the real-time performance of mapping cannot be guaranteed.

To sum up, the technical solutions for 3D environmental mapping provided in the prior art have the problem of a large amount of computation and cannot guarantee real-time mapping

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