Abstract
The existing ultrasonic obstacle avoidance robot only uses an ultrasonic sensor in the process of obstacle avoidance, which can only be avoided according to the fixed obstacle avoidance route. Obstacle avoidance cannot follow additional information. At the same time, existing robots rarely involve the obstacle avoidance strategy of avoiding pits. In this study, on the basis of ultrasonic sensor obstacle avoidance, visual information is added so the robot in the process of obstacle avoidance can refer to the direction indicated by road signs to avoid obstacles, at the same time, the study added an infrared ranging sensor, so the robot can avoid potholes. Aiming at this situation, this paper proposes an intelligent obstacle avoidance design of an autonomous mobile robot based on a multi-sensor in a multi-obstruction environment. A CascadeClassifier is used to train positive and negative samples for road signs with similar color and shape. A multi-sensor information fusion is used for path planning and the obstacle avoidance logic of the intelligent robot is designed to realize autonomous obstacle avoidance. The infrared sensor is used to obtain the environmental information of the ground depression on the wheel path, the ultrasonic sensor is used to obtain the distance information of the surrounding obstacles and road signs, and the information of the road signs obtained by the camera is processed by the computer and transmitted to the main controller. The environment information obtained is processed by the microprocessor and the control command is output to the execution unit. The feasibility of the design is verified by analyzing the distance acquired by the ultrasonic sensor, infrared distance measuring sensors, and the model obtained by training the sample of the road sign, as well as by experiments in the complex environment constructed manually.
Highlights
With the development of artificial intelligence technology, mobile robots are widely used in intelligent factories, modern logistics, security, precision agriculture and other aspects [1,2,3,4]
The most important thing to realize the autonomous motion control of a mobile robot is to obtain the information of the surrounding environment and transfer it to the main controller to convert it into control command, so as to ensure that the robot can safely and stably avoid all obstacles while moving to the destination, which can be achieved when the mobile robot has a strong perception system
In the physical prototype experiment, the mobile robot can pass through narrow gap between obstacles stably and safely, and can run correctly according to thethe direction gap between obstacles stably and safely, and can run correctly according to the direction gap between andreach can run according to the direction indicated by obstacles the roadstably signsand andsafely, the correctly given destination position
Summary
With the development of artificial intelligence technology, mobile robots are widely used in intelligent factories, modern logistics, security, precision agriculture and other aspects [1,2,3,4]. The sensing technologies of mobile robots include passive sensing based on multiple cameras, stereo vision and infrared cameras and active sensing using lidar and sonar sensors to detect dynamic or stationary obstacles in real time [11]. The early method of obstacle avoidance and path planning is to detect the stickers on the ground by infrared ray for navigation. This method can only be used in a known environment. [14] Jiang et al [15] utilized six ultrasonic sensors to capture relative information about of ambient wheeled robots and to identify a parking space for automatic parking. After solving the above problems, the function of road sign recognition is introduced, which allows the mobile robot to make accurate movement based on the traffic sign information
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