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Mobile robot is a comprehensive system integrating environment perception, dynamic decision-making and planning, behavior control and execution. It integrates multi-disciplines such as sensor technology, information processing, electronic engineering, computer engineering, automation control engineering and artificial intelligence. Research results. Mobile robots can not only accept human command, but also run pre-programmed programs, and they can also act according to the principles and programs formulated with artificial intelligence technology.

In recent years, China's population birth rate has continued to decline, and the demographic dividend of the manufacturing industry has gradually disappeared. The industries that originally enjoyed the demographic dividend brought by China's high birth rate, such as 3C electronics, logistics, and automobile manufacturing, all face problems of low labor rates and low productivity.

Therefore, as a major substitute for human resources, the demand for mobile robots (AGVs) has become increasingly strong. At the same time, with the rapid development of logistics systems, the performance of robots has been continuously improved, and the application scope of mobile robots has been greatly expanded. Whether it is a wide variety of heavy materials or finished products in production and storage, or the explosive growth of express parcels in logistics sorting, the current mobile robot technology has reached a time window that can be applied in batches. But there are still certain problems. The limited scope of work, limited business coverage, limited service provision, and high operation and maintenance costs are the major challenges facing mobile robots.

Autonomously positioned robots face challenges

Faced with the current difficulties of mobile robots, the fundamental reason is that key technologies (long-term autonomous movement and large-area coverage movement) have not been well broken through.

During operation, mobile robots need to cover a large area, so a lot of data is needed to describe different environments. At the same time, mobile robots are required to adapt to dynamic scenarios. For example: when mobile robots detect and track static or dynamic objects, they must learn more knowledge to predict changes in the environment.

Not only that, mobile robots need to run for a long time, and more and more data storage requirements. Therefore, it requires more storage space and stronger computing power, but it is difficult to achieve if it is only relying on the single body of the robot.