Path planning and obstacle avoidance method and system based on laser radar and depth camera

Abstract

The invention provides a path planning and obstacle avoidance method and system based on a laser radar and a depth camera, and the method comprises the steps: enabling the laser radar and the depth camera to be disposed on an AGV movement platform, and obtaining an AGV movement track model according to a preset central processing system in the AGV movement platform; reconstructing a position environment according to the laser radar, and obtaining environment layout data; monitoring the overall operation condition of the surrounding environment of the AGV moving platform according to the depth camera; and constructing an AGV motion platform autonomous obstacle avoidance algorithm based on the laser radar and the depth camera according to the environment layout data and the overall operation condition, and determining a target optimal path.

Description

technical field [0001] The present invention relates to laser SLAM, path optimization algorithm, autonomous obstacle avoidance algorithm and many other field technologies, and is committed to developing a method and system for path planning and obstacle avoidance based on laser radar and depth camera. Background technique [0002] At present, simultaneous positioning and map construction usually refers to a system that collects and calculates various sensor data on an AGV car or other carriers to generate its own position and posture positioning and scene map information. SLAM technology is the key to the action and interaction capabilities of AGV cars or other intelligent bodies. It has a wide range of applications in the fields of automatic driving, service AGV cars, drones, AR / VR, etc. It can be said that anyone with certain action capabilities Agents all have some form of SLAM system. The emergence and popularization of lidar makes measurement faster and more accurate, ...

AI Technical Summary

Problems solved by technology

However, with the development of digital industry, pure SLAM mapping can no longer meet the needs of high-level functions such as autonomy and intelligence of AGV cars in various industrial scenarios. For example, in unmanned workshops, not only AGV cars are required to follow a fixed trajectory For cargo transportation and deployment, it is also required that the car can be adjusted and dispatched in time when an accident occurs, so as to minimize the economic loss caused by the accident. This requires the AGV car to have independent path planning, autonomous obstacle avoidance, and intelligent control. and other all-round intelligent functions

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