Autonomous Floor Cleaning Prototype Robot Based on Image Processing

Transcription

1 Autonomous Floor Cleaning Prototype Robot Based on Image Processing A.Charles, 1 PG Scholar, Kumaraguru College of Technology, Coimbatore, India Varunac1186@gmail.com Dr. Rani Thottungal, 2 Head of the Department Kumaraguru College of Technology, Coimbatore, India hod.eee@kct.ac.in Abstract In this Paper, Floor Cleaning Process is to be made automated so that it eases the time for the humans. The images from the camera are taken at regular intervals for image processing. In image processing the robot and the spilt sauce are located and the distance between them is calculated in image coordinates. Image coordinates are converted to world coordinates by calibrating the camera and the values sent to the robot through Bluetooth. The robot reaches the sauce by obtaining distance values to the destination for cleaning. Keywords: Image processing, Matlab, Autonomous, Camera Calibration. 1. INTRODUCTION The robot market is estimated to grow into about ten times as large as the current scale for twenty years in the future. Autonomous mobile robots for the floor cleaning purpose would acquire greater importance in order to clean efficiently without any human intervention. The adequate integration of hardware and software for image processing is designed for the robot vision system. Home appliance robotics research is becoming active more than ever. So far several number of big Heavy cleaning mac9hines are available for domestic and industrial use.but their operations are non-autonomous type and these can perform only some specific functions of cleaning. The solution is found for this to optimize the energy cleaning only in the required place using camera calibration parameters and driving the robot with the distance parameters sent through Bluetooth. 2. IMPLEMENTATION DETAILS The camera used here is mobile camera which captures the image of the floor. Which acts a ipcam and the image is store for processing in Matlab.The new object is found and the distance is calculated from the robot and corresponding values are sent to robot with Bluetooth A. TM4C123G Microcontroller The TIVA C Series TM4C123G Launch Pad is used as the controller which gets the distance values to the new object found interfaced to Bluetooth. The controller based on the distance values drives the robot accordingly. The software is written in C language using CCS IDE and written to controller ROM. B. HC-05 Bluetooth HC-05 module is used for SPP(Serial Port Protocol)which sets up a wireless connection with the Matlab for the reception of data.these data is used for controlling the robot. C. L293D L293D is a typical Motor driver.this can be used to control the motor direction in either way.this also acts as an insulator protecting your controller from the induced voltage from the motor. Hardware The module consists of the prototype robot with chassis and two wheels attached, the wheels run with the help of DC motor driven by L293D.A DC motor to which circular mob is attached acts as a sweeper. The motor is powered by an external 12V battery. The Launchpad is powered with the same power supply. D. UART communication A serial interface that is used for communication between TM4c123 and the HC05 module.both Half Duplex and full Duplex mode are supported for sending and receiving the data. E. Camera Calibration Camera resectioning, that estimates the parameters of the image sensor and lens of an image or video camera, these parameters are used to correct lens distortion, determine the location of the camera in the scene or measure the size of an object in world units. Camera parameters that include extrinsic,intrinsic, and distortion coefficients. Camera parameters is estimated using the 3-D world points and their corresponding 2-D image points. You can use images of a checkerboard and find these parameters. F. Pinhole Camera Model A pinhole camera with a single small aperture is a simple camera without a lens and light rays pass through the aperture to project an inverted image on the opposite side of the camera. A virtual image plane is placed in front of the camera and containing the upright image of the scene. 1

2 the calibration algorithm. A transformation from 3-D world coordinate system to the 3-D camera's coordinate system is the required extrinsic parameters. Projective transformation is done from the 3- D camera's coordinates into the 2-D image coordinates for the intrinsic parameters. The pinhole camera outputs 4-by-3 camera matrix. This matrix maps the image plane to the 3-D world scene. The calibration algorithm calculates the camera matrix using the intrinsic parameters and extrinsic The extrinsic parameters is the location of the camera in the 3-D scene. The intrinsic parameters are the focal length and optical centre of the camera. Extrinsic Parameters A rotation, R, and a translation T is used for the intrinsic parameters,the camera's coordinate system origin is at its optical center and the image plane is its X and Y plane. Using the extrinsic parameters,the world points are transformed to camera coordinates.using the intrinsic parameters, the camera coordinates are mapped into the image plane. Intrinsic Parameters The intrinsic parameters are the optical centre, also known as the principal point, and the skew coefficient and the focal length. ALGORITHM 1.Read the input image file. 2.Resize the image file to match the Matlab data size. 3.RGB color image is converted to grayscale for image pre-processing. 4.The Grayscale image is converted to Binary Image. 3. METHODOLOGY Camera Calibration Parameters The camera matrix using the extrinsic and intrinsic parameters is calculated using 5.Image thresholding is done as a part of image pre processing 6.Image segmentation is done, bounding box is used to segment each object in the image. 2

3 7.Bounding box dimensions, parameters are taken for the object area to be covered by the robot. 8.To match the image parameters with the real world, Camera calibration has to be done. 9.After calibrating converting image coordinates to world coordinates. 10.The distance values are sent to robot with Bluetooth. 11.The controller drives the motor to the first point and turns 90 degrees. 12.The final destination point is reached & it starts the DC motor in which mob is attached for cleaning. 4. DESIGN OVERVIEW The functional block diagram illustrate the how the component interact with each other and execute the desire operation. Fig.1 Block diagram of proposed system 5. SOFTWARE DESCRIPTION The CCS v6 IDE is used to program the TM4C123 LP and to interface with the Bluetooth.The software simulation has been successfully implemented in Matlab.The Main Goal is to identify the object in the image and to segment the image.the matab toolbox helps to find the image dimensions and to find the distance between the objects with the appropriatealgorithm 6. EXPERIMENTAL RESULT Fig.1 Distance Between Robot and Object in Image Coordinates 3

4 Fig.2 Reproduction Errors for Camera Fig.3 Camera Calibration Values & Result in World Coordinates Hardware results Fig.4 Hardware 7. CONCLUSION This paper describes the design and implementation of autonomous floor cleaning robot. The image processing is used to identify object and the robot.the Distance between them is calculated in image coordinates.camera calibration done with Matlab to find World coordinates.the Obtained Value is sent to the Robot with Bluetooth, and the controller drives the robot with the received Values. REFERENCES 1. Zhang, Z. "A Flexible New Technique for Camera Calibration." IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 22, No. 11, 2000, pp

5 2. Heikkila, J., and O. Silven. "A Fourstep Camera Calibration Procedur e with Implicit Image Correction." IEEE International Conference on Computer Vision and Pattern Recognition Bradski, G., and A. Kaehler. Learning OpenCV: Computer Vision with the OpenCV Library. Sebastopol, CA: O'Reilly, Bouguet,J.Y."Camera Calibration Toolbox for Matlab."Computational Vision at the California Institute of Technology.Camera Calibration Toolbox for MATLAB. A.Charles was born in coimbatore, Tamil Nadu state, India in He completed her Bachelor s degree in the department of ECE at SNSCT, coimbatore. He is currently working towards the Master s Degree in Embedded system technologies at Kumaraguru college of technology, Coimbatore, Tamil Nadu state, India. Dr. Rani Thottungal, She completed her Bachelor s degree in the department of EEE at Andhra University. She completed her Master s degree in Power Systems in the department of EEE at Andhra University. She Completed her Doctor of Philosophy in the department of EEE at Coimbatore Institute of Technology. He is currently working as Professor & Head in the department of EEE at Kumaraguru college of technology, Coimbatore, Tamil Nadu state, India. 5