Motion Control And Target Grabbing Of Mobile Manipulator Based On Machine Vision

Currently,Mobile Manipulators is a classic wheeled mobile robot.Compared with traditional industrial robots,the addition of intelligent trolleys expands the working space of traditional robotic arms.The increase of machine vision makes it capable of autonomous sensing,decision-making and execution.This article first purchased the chassis,robot arm,vision camera,main control chip and other equipment according to the design requirements of the project,and independently designed auxiliary hardware devices such as the driver board and the trolley plus board,and finally completed the assembly and debugging of the corresponding hardware equipment.The main research content of this paper is the motion control and target grabbing of mobile robots based on machine vision.The research work is mainly carried out from the following aspects:(1)Taking the monocular binocular vision system as the research object,researching the machine vision target recognition and positioning,designed a single binocular vision positioning method based on the target edge ratio fusion method to achieve accurate positioning of the target grabbing position.The monocular vision system establishes a global spatial positioning model based on the principle of monocular vision to achieve target positioning and obstacle recognition.The binocular vision system is based on the BM matching algorithm and uses color filtering optimization methods to complete the spatial positioning of the target object.Finally,a single binocular vision positioning experiment based on the target object edge proportional fusion method was carried out to achieve accurate positioning of the target object.(2)Taking the manipulator as the research object to study the space kinematics control of the manipulator,firstly,the forward kinematics model of the manipulator is established based on the DH model,the working space of the manipulator is analyzed,and then the steering gear is used based on the principle of minimum energy consumption The optimization method is limited,and the space inverse kinematics is optimized and solved for the space target point.Finally,the manipulator gripping experiment is completed.(3)Taking the steering car as the research object,to study the movement trajectory control of the steering car,firstly,the car motion model is established based on Ackerman steering geometry,and the pure tracking algorithm is improved by the mileage correction method,and the path trajectory is completed by the PRM algorithm Planning,and finally use the improved pure tracking algorithm according to the results of path planning to complete the simulation and experimental research of the car trajectory control.Finally,taking the whole vision mobile robotic arm as the research object,first complete the debugging of the experimental equipment,design the system workflow according to the set experimental process,design and implement the software,and realize the independent and autonomous operation control of the mobile robotic arm based on machine vision At last,we carried out several experimental simulation tests and analysis to verify the precise positioning,trajectory obstacle avoidance and stable grasping of the visual mobile robot arm optimized by visual fusion and tracking improved algorithms.