OBSTACLE MONITORING & DETECTION BASED CRUISE CONTROL SYSTEM
Soban Saeed
Dept. of Electrical Engineering, National University of Sciences & Technology, Rawalpindi, Pakistan
Abstract: Autonomous Obstacle Avoidance Robotics
Industries increasingly use robots for high performance and reliability. Obstacle avoidance robotics detects and prevents collisions, creating autonomous robots. Designing these robots requires integrating various sensors, with obstacle detection being primary. Sensors like bump, infrared, and ultrasonic are used, with ultrasonic being most suitable due to its low cost and high ranging capability.
This system uses an ultrasonic sensor to detect obstacles and an Arduino Uno microcontroller for control. The sensor sends commands to the microcontroller, which then actuates motors via a motor driver to redirect the robot, ensuring autonomous movement.
Keywords—Obstacle avoidance, Cruise control, Arduino, Ultrasonic sensor, robot, DC motors.
Introduction: The Evolution of Mobile Robotics
Mobile robots are increasingly integrated into military, medical, space exploration, and domestic settings. Obstacle avoidance and path recognition are crucial for autonomous navigation without human intervention. Early methods used radar, infrared (IR), and ultrasonic sensors. Radar proved most suitable due to environmental constraints affecting IR and ultrasonic sensors.
Other sensors extract plant features for characterization, aiding autonomous fertilization. Cameras assist navigation and obstacle detection for meteorite searches and planetary rovers, though they require adequate illumination. Sonar was used for localization and navigation, but a single sensor is often insufficient, requiring multiple rings for optimal performance.
This study focuses on designing a simple, cost-effective obstacle avoidance system. Electric vehicles use electric motors and batteries for power. MATLAB and Simulink are used for automated driving functionality, reducing design cost and time.
Software Implementation & Logic
The system's software is implemented in C language using Arduino IDE. The robot's flowchart shows sensors activating when the motor moves forward. The ultrasonic sensor transmits a 37 KHz sound, awaiting an echo to calculate obstacle distance.
If an obstacle is detected within 40m, the servo turns 90 degrees to check for clear paths. If the ultrasonic sensor detects an obstacle, the motor rotates anticlockwise, then turns right, and continues forward. If all directions (left, forward, backward) are blocked, the robot reverses and repeats the process.
Data Collection, Signal Processing & Chassis Design
Data Collection
The ultrasonic sensor reads environmental data, sending digital information to the microcontroller for processing. A single ultrasonic sensor on top of the robot follows pavement, turning at wall ends.
Signal Processing
Analog sensor data (distance values) are connected to Arduino's analog pins. The microcontroller processes this data using programmed instructions to control DC motor direction and speed.
Chassis Design
The robot features plastic plates with two rear wheels attached to DC motors and a front wheel. The ultrasonic sensor is mounted on a servo to rotate and detect obstacles.
Working Principle
The robot continuously monitors surroundings with an ultrasonic sensor on a servo. It moves forward until an obstacle is detected within a threshold (e.g., 50 cm), then stops. The servo scans left and right to find the clearest path, turning accordingly. The robot resumes forward movement, repeating the process. Distance and speed are displayed on an LCD, enabling autonomous navigation and collision avoidance.
Analysis & Understanding Achieved
Conclusions
This project successfully developed a simple, cost-effective obstacle detection and avoidance system for an unmanned land mover using an ultrasonic sensor. It achieved accuracy and minimal failure probability, demonstrating collision avoidance and position change. The design allows for added functionalities and remote control via an IR receiver. This system is valuable for hostile environments, defense, and security sectors.
Final Demonstration
The final demonstration rigorously tested the obstacle avoidance robotics system in a simulated real-world environment. Our objective was to validate its navigation capabilities and responsiveness to unexpected obstacles.
The robot successfully detected and avoided various obstacles, showcasing its precise sensor integration and robust control logic. Real-time feedback from the LCD confirmed accurate distance measurements and adaptive motor adjustments. This comprehensive validation affirms the system's effectiveness and reliability for autonomous operation.