Robotics Course Overview

Course Overview

This course provides a thorough introduction to robotics, covering the fundamental principles, design, programming, and applications of robotic systems. Students will explore various aspects of robotics, including mechanical design, sensor integration, control systems, and artificial intelligence. The course combines theoretical knowledge with hands-on projects to provide a practical understanding of robotics.

Course Objectives

By the end of this course, students will be able to:

1. Understand the fundamental principles of robotics.
2. Design and build robotic systems.
3. Program robots for various tasks and applications.
4. Integrate sensors and actuators into robotic systems.
5. Apply advanced control techniques and AI to robotics.
6. Evaluate the ethical and societal impacts of robotics.

Course Outline

Module 1: Introduction to Robotics

• Overview of robotics and its history
• Types of robots and their applications
• Key components of robotic systems
• Introduction to robotics terminology and concepts

Module 2: Mechanical Design of Robots

• Fundamentals of robot kinematics and dynamics
• Robot arm design and degrees of freedom
• Mobile robot design: wheels, tracks, and legged systems
• Materials and structural considerations

Module 3: Sensors and Actuators

• Types of sensors: proximity, vision, accelerometers, gyroscopes, etc.
• Sensor integration and data acquisition
• Types of actuators: motors, servos, pneumatics, and hydraulics
• Actuator control and power considerations

Module 4: Robot Programming

• Introduction to robot programming languages (Python, C++, ROS)
• Writing and debugging robot control software
• Programming for task automation and decision making
• Simulation environments (e.g., Gazebo, V-REP)

Module 5: Control Systems and Navigation

• Basics of control theory: PID, feedback, and feedforward control
• Path planning and trajectory generation
• Navigation algorithms for mobile robots
• Obstacle detection and avoidance

Module 6: Artificial Intelligence in Robotics

• Introduction to AI and machine learning concepts
• Applying AI for robot perception and decision making
• Reinforcement learning for robotic control
• Case studies of AI in robotics applications

Module 7: Advanced Topics in Robotics

• Collaborative robots and human-robot interaction
• Swarm robotics and multi-robot systems
• Robotic vision and image processing
• Autonomous systems and self-driving vehicles

Module 8: Ethics and Societal Impact

• Ethical considerations in robotics
• Legal and societal implications of robotic systems
• Robotics in healthcare, industry, and daily life
• Future trends and the evolving role of robotics in society

Module 9: Capstone Project and Final Assessment

• Students work on a comprehensive capstone project involving robotic design, programming, and application
• Project presentations and peer evaluations
• Final exam covering theoretical and practical knowledge
• Course wrap-up and discussion of future learning paths