PC-based mobile robot navigation sytem
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The document describes the design and components of a PC-based mobile robot for navigation. It uses a vision system with image processing and feature matching to navigate. A fuzzy logic controller computes the speed and angular speed needed by the two motors. An obstacle avoidance algorithm detects obstacles using pixel appearance differences. The robot is powered by a 12V battery and controlled through a software interface on a PC. Testing showed the fuzzy controller could achieve desired turns to navigate autonomously.
PC-based mobile robot navigation sytem
- 1. PC-Based Mobile Robot for Navigation Ankit Surti 325
- 2. Introduction… The navigation system plays very an important role and challenging competence for mobile robot.Navigation of mobile robot includes a variety of theories and technologies such odometry technique, ultrasonic mapping, and vision system. In the application of navigation, it consists of two areas: global navigation and local navigation. Global navigation such as GPS (Global Positioning System) and INS (inertial Navigation System) is often used in various open areas. Meanwhile, local navigation such as vision techniques are very effective base in the closed range navigation. Navigation using vision approach has many tasks, including target matching, target identification and others. Practically, the use of optical sensors and image processing are the major factors affecting the accuracy of navigation. In navigation application, a mobile robot must interpret its sensors data to extract environment information, with which the mobile robot can determine its position. After mobile robot can localize its position, it must decide how to act to achieve its purpose. Lastly, the mobile robot must control its drive system to achieve the desired path. The increment distance of the robot’s movement sensed with wheel encoders is integrated to calculate position.
- 3. Context… Working prototype of the PC-based mobile robot 1.Vision Sensing This work presents an approach using computer vision which applied feature matching technique after the image has been proceeds by Canny edge detector. Features like circular marking, the distance between two vertical lines used by the fuzzy system to analyze whether it has relation with the door being analyzed to design an expert system to detect rectangular shaped door. In this study, vision system is applied to extract the information such as the distance of target and the orientation of target.
- 4. Circuit Diagram… Interface-cum-driver circuit for the PC-based mobile robot Power supply circuit
- 5. 2.Mobile Robot Control System The posture provides information about how the mobile robot moves with respect to the floor Fuzzy Logic Controller:The master controller is a fuzzy logic controller (FLC) which computes the required speed and angular speed needed by the two m otors to drives the robot for target trajectory. Obstacle Avoidance Algorithm:Our obstacle avoidance algorithm uses the princ iple of appearance-based obstacle detection. According to this principle,any pixel that differs in appearance from the ground is classified as an obstacle.This method is based on three assumptions that are reasonable for a variety of indoor and outdoor environments: 1. Obstacles differ in appearance from the ground. 2. The ground is relatively at. 3. There are no overhanging obstacles. 3.Power System The vehicle electronics, including the onboard computer and the drive motors, are powered by an uninterrupted power supply (UPS) running on a 12V dry battery. On a full charge,the battery can keep the robot running for approximately 30 minutes. An AC/DC converter is used to provide 9V input tothe drive motors. As the UPS comes with a surge protection Socket.
- 6. PCB Bottom View Top View
- 7. The Software for Controls The software program for the user interface to control the robot (Mobilerobot.exe) is designed in Visual Basic6.0. The core file used by software is ‘inpout32.dll,’ which can be downloaded from ‘www.l ogix4u.net’ for free.The .dll file uses a kernel-mode driver.Therefore this software works as good with NT-based Windows OS as with WinXP and Win2000.A separate program module for the inpout32.dll isused along with the main program of the mobile robot. For details about the .dll file, visit ‘www.logix4u.net’.The software uses timer controls to produce delay in between the counting sequence that controls the speed of the stepper motors.
- 8. Component List 1.Semiconductors: IC1-IC8 - MCT2E opto-coupler IC9 - ULN2803 buffer/driver IC10 - 7812 12V regulator D1-D4 - 1N4001 rectifier diode LED1 - 5mm light-emitting diode 2.Resistors (all ¼-watt, ±5% carbon): R1 - 1-kilo-ohm R2-R9 - 470-ohm 3.Capacitors: C1 - 1000μF, 35V electrolytic C2 - 0.1μF ceramic 4.Miscellaneous: X1 - 230V AC primary to 15V, 1A secondary transformer CON1 - 25-pin, D-type, parallel-port male connector SM1, SM2 - 12V, 7.5deg/step stepper motor - 8-conductor ribbon cable (3.5 metres in length) - Two wheels for right and left side of the robot - One castor wheel for front - Two side brackets for stepper motor support - One chassis board - One webcam or PC camera with USB interface cable - Nuts and bolts - 2-pin SIP connector (male and female) - Two 5-pin SIP male connector - DC socket and plug
- 9. Working… MCT2E is the most popular integrated circuit used for isolating high-voltage circuits from low-voltage circuits. Used to protect the parallel port from damage, it is an opto-coupler having an internal photo transistor and an LED. The LED glows when it receives high output pulse from the parallel port. The transistor conducts when its base receives light from the lated 12V DC is connected to ULN2803 driver IC. In place of the power supply circuit shown in Fig. you can also use a 12V, 4.5Ah battery to power the main circuit. Two stepper motor are used for moving and turning the robot.Each of these stepper motors has five wires for connecting to the driver circuit. Out of the five wires,four wires emerge from coils of the stepper motors and the fifth is the centre-tapped common terminal.Correct identification and connection of these wires is important for successful assembly of the stepper motor. The unipolar stepper motor has two centre-tapped coils.Their centre tapped terminal are joined to make one common terminal. Connect these coils to the output termina ls of the driver circuit in sequence. Then the Robot work on 3 main factors: 1.Direction Control 2.Speed Control 3.Camera View
- 10. Advantages Ours is a Wireless ROBOT with Wireless Movements. Ours is an industrial ROBOT, Controlled by the PC . It is also a Mobile Robot which has got certain artificial intelligence feature . Our ROBOT will pick the Objects and will place it in another place. Another unique concept about our ROBOT is that it can serve any fire and detect the fire. Consistency of performance. 240 continuous working. Reduced cycle times. Reduced amount of operator errors. Improved quality of product.
- 11. Disadvantages High standard of maintenance required Precise programming needed (time, training, specialist knowledge) when computer systems failure will cause breakdown New products require complete reprogramming Certain processes still need a skilled operator Complex and expensive equipment to buy and install
- 12. Conclusion… Landmark recognition is not an easy task but it is very important area in developing mobile robots that is need to accomplish positioning, path planning and navigation. A robot vision system using fuzzy logic technique to identify the object in real time was presented. The system is able to find and recognize the circle and then calculate the position of the robot to navigate in a laboratory. The technique used is based on image processing and optimization in real time. It hard to an able a mobile robot navigates in indoor environment. The output is very useful for a mobile robot in real time to find and detect objects. Usually a robot vision system is very slow due to computational time used for image processing. Image processing time was minimized by the techniques used and the detection of object can be done about less than 1 second.
- 13. Conclusion… An analysis and design of fuzzy control law for steering contr ol of the developed non-holonomic mobile robot are presented. The proposed fuzzy controller is implemented on the developed mobile robot. The system can perform and satisfactory results are obtained which show that the proposed fuzzy controller can achieve the desired turn angle thus it can make the autonomous mobile robot moving to the target. The control system need PID controller to guarantee the stabil ity of the straight conveying and turning trajectory.