A real-time multi-sensor community robot navigation method

Abstract

The invention provides a real-time multi-sensor community robot navigation method, which belongs to the field of robot navigation. The present invention first obtains the direction and distance between every two points through a given starting point, a series of intermediate points and end points, and generates multiple walking segments, and the community robot walks according to the walking segments; each cycle detects laser radar and camera data, Make the community robot reasonably avoid obstacles and stay away from the roadside; combine the physical mileage and GPS information, filter and correct the position information, determine whether the community robot has completed the distance of each walking segment, and automatically enter the next walking segment after completing a walking segment. End the navigation until the last walking segment is completed, so that the movement of the community robot is more precise and the positioning is more accurate; set the emergency area, once there is an obstacle in the emergency area, start emergency processing, avoiding the collision between the community robot and other objects and pedestrians , ensuring its safety.

Description

technical field [0001] The invention belongs to the field of robot navigation, in particular to a real-time multi-sensor community robot navigation method. Background technique [0002] With the continuous improvement of urban intelligence, intelligent robots are becoming more and more popular. All walks of life are constantly developing intelligent robots suitable for the industry, hoping that they can replace manual labor to complete repetitive, cumbersome, and dangerous operations, or just reduce costs. Community robots can replace manual tasks such as security inspections, vehicle identification, and community service provision, so they have become more and more popular in recent years. As the underlying application of community robots, autonomous navigation has become an essential part of it. [0003] At present, most outdoor robot navigation systems either rely on many high-precision sensors, which are very expensive, or only use vision for navigation, which is compl...

AI Technical Summary

Problems solved by technology

[0003] At present, most outdoor robot navigation systems either rely on many high-precision sensors, which are very expensive, or only use vision for navigation, which is complex to implement, and has many restrictions on lighting, weather, ground and other environments, and has low practical value.

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