Research On Vision-based Target Detection And Path Planning Of Mobile Robots

With the continuous improvement of the technology,the autonomous operation ability of intelligent robots has gradually become a research hotspot in various industries.Path planning and dynamic obstacle avoidance of mobile robots are an important research content to realize robot autonomous operation.During the robot movement,sensors are used to perceive the robot's working environment to provide the robot with a collisionfree safe path to help the robot reach the target destination.In this paper,the path planning in the complex environment of the robot is the research point,and the key technologies involved in the path planning of the robot are studied.The main research contents are as follows:(1)Research on dynamic obstacle detection of mobile robots based on improved optical flow method.In the process of robot path planning,when the operating environment changes,the robot may not be able to reach the target destination smoothly Therefore,the surrounding environment information is collected through the robot's visual sensor,first used the three-frame difference method to obtain the movement area of the dynamic obstacle in front of the machine,filterd the complex background environment,and then detectd the front dynamic obstacle by the modified optical flow method.The optical flow method detects the accuracy of dynamic obstacles,and uses the depth information of optical flow to calculate the collision time between the robot and the obstacle feature points using the depth information of optical flow to judge the distance between the robot and the dynamic obstacle based on the distance for improving the accuracy.(2)Research on the robot static path planning algorithm.The static path planning of the mobile robot is the basis for the robot to reach the target destination smoothly in a complex environment,but the traditional firefly algorithm may fall into a local optimum during the path selection process,and it may appear premature and cannot find the optimal path.Therefore,according to the attraction characteristics of the firefly,the maximum attraction coefficient of the firefly is adaptively controlled,and the firefly step length factor that affects the optimization is modified,which enhanced the optimization ability of the improved firefly algorithm in the static path planning of the robot.(3)Obstacle avoidance research of optical flow balance method.Combined with the static path planned by the firefly algorithm and the dynamic obstacle detection of the improved optical flow method,the relative distance between the obstacle and the robot in the forward direction is detected through the optical flow field.The optical flow balance horizontal obstacle avoidance method is used to realize dynamic obstacle avoidance to improve the accuracy and safety of path planning.