Multi-sensor-based autonomous obstacle avoidance navigation system

Abstract

The invention provides a multi-sensor-based autonomous obstacle avoidance navigation system. The multi-sensor-based autonomous obstacle avoidance navigation system comprises a sensor processing layer, a local algorithm processing layer, an error detection layer and a central processing layer, wherein the sensor processing layer comprises a plurality of sensor processing nodes; the local algorithm processing layer comprises a plurality of algorithm calculation nodes; the error detection layer is used for detecting hardware and software faults of a detection system and shielding nodes with faults when determining that the sensor processing nodes and / or the algorithm calculation nodes have faults; and the central processing layer is used for carrying out overall optimization on results of the plurality of algorithm calculation nodes in the local algorithm processing layer. The multi-sensor-based autonomous obstacle avoidance navigation system adopts a non-centralized type fusion design so that the robustness and the fault tolerance of the system are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of autonomous obstacle avoidance navigation of robots and unmanned aircraft, and in particular relates to the design and method of an autonomous obstacle avoidance navigation system that can automatically select different sensor combinations according to changes in the external environment. Background technique [0002] With the advancement of science and technology, the application fields of robots and unmanned aerial vehicles are becoming more and more extensive. They can not only provide various services (such as household service robots, sweeping machines, etc.), but also perform various tasks in complex and dangerous environments (such as robots entering the Fukushima nuclear power plant accident site in Japan to detect internal damage, drones, etc.) Aerial photography of post-disaster scene, etc.). However, quite a lot of applications are still completed under manual remote control. In order for robo...

AI Technical Summary

Problems solved by technology

However, the two-dimensional grid map has its limitations. It only contains cross-sectional information at a certain height in the scene. The lack of information will affect the robot's obstacle avoidance function and limit the robot's automatic navigation.

Furthermore, such maps are almost impossible to use on drones

[0012] At present, the design of autonomous obstacle avoidance navigation systems and methods is often limited to the application occasions. For each different application occasion, according to the different types and collocations of sensors, the specific obstacle avoidance navigation systems and methods are also correspondingly different, which leads to the need to design A variety of different obstacle avoidance navigation systems and methods; at the same time, if a sensor fails, the obstacle avoidance navigation system and method will not be able to adapt well, making the entire system less robust

At present, there is no universal autonomous obstacle avoidance navigation system and method with good adaptability and high fault tolerance

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