Multi-sensor-fused low-speed unmanned vehicle detecting obstacle avoidance system

Abstract

The invention belongs to the technical field of unmanned driving and discloses a multi-sensor-fused low-speed unmanned vehicle detecting obstacle avoidance system. The multi-sensor-fused low-speed unmanned vehicle obstacle avoidance system comprises a control system and a vehicle roof laser radar and further comprises a front laser radar set and a back laser radar set which are configured on the lower portion of an unmanned vehicle body. The vehicle roof laser radar is used for detecting fluctuation of a road in front of an unmanned vehicle and detecting the condition of obstacles in a movement path in front of the unmanned vehicle with the front laser radar set. The front laser radar set is further used for detecting the condition of obstacles in a front left movement path and a front right movement path of the unmanned vehicle. The back laser radar set is used for detecting the condition of obstacles behind the unmanned vehicle. The control system comprises an upper computer and a lower computer, the upper computer receives feedback signals of all the laser radars in real time, conducts decoding, then communicates with the lower computer and transmits input control signals to thelower computer, and the lower computer decodes the input control signals to control travelling of the unmanned vehicle. The multi-sensor-fused low-speed unmanned vehicle obstacle avoidance system islow in price, relatively high in cost performance, and very high in practicability.

Description

technical field [0001] The invention belongs to the technical field of unmanned driving, and in particular relates to a multi-sensor fusion low-speed unmanned vehicle detection and obstacle avoidance system. Background technique [0002] With the rapid economic development, cars have become an increasingly important part of people's lives. The negligence of drivers will lead to many accidents. About 1 million people die in traffic accidents all over the world every year. In my country, nearly 100,000 people die in traffic accidents every year. Since drivers make many mistakes, automakers must of course concentrate on designing systems that can ensure vehicle safety. Safety is one of the main factors driving the growth of demand for driverless vehicles; It’s so beautiful, letting artificial intelligence unmanned vehicles replace human driving can completely solve problems such as traffic congestion; in addition, poor air conditions are also a “catalyst” for the promotion of ...

AI Technical Summary

Problems solved by technology

[0008] (1) Since the unmanned vehicle is disturbed by unstable factors in the surrounding environment, the controller based on the single-chip microcomputer has poor anti-interference ability, and abnormalities often occur, causing the unmanned vehicle to lose control

[0009] (2) The existing unmanned vehicles all use low-level DSP and ARM series chips, and the maximum operating frequency is only about 100 MHz, which cannot meet the fast calculation of complex data of unmanned vehicles

[0010] (3) Affected by the performance of the PC of the unmanned vehicle, the data collected by the sensor of the unmanned vehicle cannot be quickly calculated and stored

[0011] (4) The data acquired by the single-line laser radar is 2D data, and information such as the height of the target cannot be distinguished. Some small objects will be ignored and eventually become obstacles. Single single-line laser radar sensor navigation has become a bottleneck in the automotive field

[0012] (5) A single single-line laser radar cannot obtain road surface information, and it needs to cooperate with other sensors to read and judge ground information

[0013] (6) Although multi-line laser radar can realize 2.5D or 3D data, can judge the height of obstacles, process ground information, etc., but the price is relatively expensive. A 64-beam laser radar can cost as much as 700,000 RMB Large-scale promotion and use

[0014] (7) A single single-line laser radar cannot detect information such as corners and road cliffs. It needs to be used with other sensors to read the surrounding obstacle signals or locate the sensor signs

[0015] (8) The current unmanned vehicles basically only consider forward detection and obstacle avoidance, and do not consider the information of obstacles in the rear. Sometimes obstacles appearing in the rear will damage the body of the unmanned vehicle, but the unmanned vehicle cannot realize Accelerate to dodge

[0016] (9) Based on a single single-line lidar unmanned vehicle, there is a detection blind spot at the moment of start-up. Once an obstacle is in the blind spot, it is easy to cause traffic accidents

[0017] (10) Unmanned vehicles based on a single single-line lidar will also have blind spots in the actual driving process. Once obstacles enter the blind spot during movement, traffic accidents will also occur

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