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Research on Painting Robot Based on Multi-sensor Fusion

Author: ZhengJiaWang
Tutor: LiuYouYuan
School: Wuhan University of Technology
Course: Mechanical and Electronic Engineering
Keywords: Painting Robot Multi-sensor fusion Kalman filter Virtual Prototyping
CLC: TP242
Type: Master's thesis
Year: 2011
Downloads: 82
Quote: 2
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Abstract


The robot is smart products developed in recent years, and set the machinery and electronic equipment. Along with the continuous development and progress of the technology of materials, machining, electronics, control, sensors, robots have been widely used in various fields. Especially with the continuous progress of China's urbanization, the painting robot increased sharply. In this context, the study of the painting robot is particularly important. Multi-sensor information fusion technology combines control theory, signal processing, artificial intelligence and other advanced theoretical and technical disciplines, the data collected through the integrated treatment of a number of sensors, enabling more accurate information obtained, with redundancy and complementarity. Multi-sensor fusion technology used in robot, can significantly improve the accuracy of the robot's control. Firstly, combined with the the painting robot work environment and the design requirements, the overall structure and material of painting robot, the structural design and the selection of the drive motor of the major joints, and parts of the three-dimensional design completed in solidworks , the overall structure of the robot assembly. Then painting robot kinematics and inverse kinematics analysis, the the painting robot's DH parameters, link coordinate system and the kinematic equations, modeling and simulation of the robot arm with the Robotics Toolbox in MATLAB toolbox. Secondly, the painting robot dynamics analysis. Solidworks create robot model imported into ADAMS ADAMS, set the equation of motion for each joint, followed by ADAMS comes solver painting robot simulation analysis to generate the data curve. Again, the multi-sensor fusion technology in robotics research. Multi-sensor information fusion technology can be integrated several sensors collect data and form a unified description of the information to the outside world, the more accurate the information obtained, can significantly improve system robustness, stability, expansion of spatial and temporal coverage ability. The paper focuses on Kalman filter system model, the algorithm processes analysis to study the speed sensor and acceleration sensor data fusion Kalman filter and Kalman filter estimate using MATLAB the acceleration deviation value analog. Finally, it discusses the RBF neural network applications in robot adaptive control. RBF neural network research the robot Cartesian coordinate ground joint position workspace transform robot neural network modeling, and on this basis, an example of a simulation of a robot of two degrees of freedom.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Robotics > Robot
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