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Robotics Laboratory (AIL332)

Robotics Lab Academic Credits

This repository contains the implementation and documentation of experiments performed as part of the Robotics Laboratory course (AIL332).

Course Information

  • Course Code: AIL332
  • Department: Computer Science and Engineering (Artificial Intelligence)
  • Category: PCC
  • Credits: 2 (0-0-3)
  • Year of Introduction: 2022

Course Outcomes

After completion of the course, students will be able to:

  1. Interface different peripherals to arduino board
  2. Assemble a mobile robot with different sensors and actuators
  3. Familiarize about localisation of mobile robots
  4. Impart intelligence to robot using standard algorithms
  5. Familiarize the robot navigation

Prerequisites

  • Basic knowledge of robotics principles
  • Programming experience in Python/C++
  • Understanding of Arduino programming
  • Familiarity with ROS (Robot Operating System)

ROS Essentials

  • Installing and Configuring ROS Environment (Kinetic/Melodic/Compatible versions)
  • ROS fundamentals (Master, nodes, topics, messages, services, parameters and actions)
  • ROS Tools – Gazebo, Moveit, Rviz
  • Creating Workspace and Package in ROS

List of Experiments

Part A: Interfacing sensors and actuators

1. Arduino Basics

2. Sensor Interfacing

3. DC Motor Control

4. Servo Motor Control

5. Sensor Calibration

Coming Soon !!!


#### 6. [Mobile Robot Assembly](./Part-A/exp6/)

#### 7. [Arduino Networking](./Part-A/exp7/)
   - GSM Integration
   - Bluetooth Communication

### Part B: Intelligent systems
#### 8. [ROS Programming Basics](./Part-B/exp8/)
   - Publisher-Subscriber Implementation
   - Service-Client Programming
   - Data Recording and Playback
   - Bag File Operations

#### 9. [Mobile Robot Localization](./Part-B/exp9/)
   - LIDAR-based Localization
   - ROS Implementation

#### 10. [Touch Sensing](./Part-B/exp10/)
    - Sensor Interfacing
    - Feedback System Implementation

#### 11. [Line Following Robot](./Part-B/exp11/)
    - IR Sensor Implementation
    - Control Algorithm

#### 12. [Obstacle Avoidance](./Part-B/exp12/)
    - Point-to-Point Navigation
    - Obstacle Detection and Avoidance

#### 13. [Object Detection](./Part-B/exp13/)
    - Algorithm Implementation
    - Testing and Validation

#### 14. [ROS Navigation](./Part-B/exp14/)
    - Turtlebot Simulation
    - Navigation Stack Implementation

Additional Programs

How to Use

  1. Clone the repository:

    git clone https://github.com/venkideshVenu/KTU-S6-Robotics-Lab-AIL332

  2. Install prerequisites:

    • Arduino IDE
    • ROS (Kinetic/Melodic/Compatible versions)
    • Required Python/C++ packages

  3. Navigate to specific experiment directory

  4. Follow instructions in individual experiment READMEs

Tools and Technologies Used

  • Arduino IDE and Arduino Board
  • ROS (Robot Operating System)
  • Python/C++
  • Gazebo, Moveit, Rviz
  • Various sensors (IR, Ultrasonic, LIDAR, Touch)
  • Motors (DC, Servo)
  • Turtlebot platform

Assessment Pattern

  • Continuous Internal Evaluation (CIE): 75 marks
  • End Semester Examination (ESE): 75 marks
  • Duration: 2.5 hours

References

  1. Siegwart, Roland, "Introduction to Autonomous Mobile Robots"
  2. Peter Corke, "Robotics, Vision and Control: Fundamental Algorithms in MATLAB"
  3. John. J. Craig, "Introduction to Robotics (Mechanics and control)"
  4. S K Saha, "Introduction to Robotics"
  5. R K Mittal and I J Nagrath, "Robotics and Control"
  6. Dahiya, Ravinder S., Valle, Maurizio, "Robotic Tactile Sensing"
  7. TurtleBot3 e-Manual: https://emanual.robotis.com/docs/en/platform/turtlebot3/simulation

License

This project is licensed under the MIT License - see the LICENSE file for details.