Robotics Course – Content Outline

Course Overview

This course introduces students to advanced robotics concepts, integrating mechanical design, electronics, programming, and AI applications. Students will develop hands-on experience building and programming robots, working on autonomous and intelligent systems, and applying robotics principles to solve real-world problems.

Learning Outcomes:

• Design and build functional robots with mechanical and electronic components

• Program robots for autonomous behavior using sensors and AI

• Apply principles of control systems, robotics algorithms, and mechatronics

• Analyze and troubleshoot hardware and software systems

• Collaborate on robotics projects with real-world applications

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Module 1: Introduction to Robotics

• History and evolution of robotics

• Types of robots (industrial, service, mobile, humanoid, autonomous)

• Applications in industry, healthcare, space, agriculture, and entertainment

• Basic terminology: actuators, sensors, microcontrollers, end-effectors

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Module 2: Mechanical Design & Kinematics

• Robot structures: wheels, legs, arms

• Degrees of freedom (DOF) and mobility

• Introduction to kinematics: forward and inverse kinematics

• Grippers, manipulators, and end-effector design

• CAD modeling basics for robotics components

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Module 3: Electronics & Sensors

• Introduction to microcontrollers (Arduino, Raspberry Pi)

• Motors and actuators (servo, DC, stepper motors)

• Sensors: ultrasonic, IR, LIDAR, gyroscope, accelerometer

• Circuits and power supply design for robotics

• Reading sensor data and interfacing with microcontrollers

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Module 4: Programming for Robotics

• Robotics programming languages: Python, C++, or Arduino IDE

• Control loops and logic

• Integration of sensors and actuators

• Motion planning and navigation basics

• Simple AI and machine learning applications in robotics

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Module 5: Control Systems & Automation

• Open-loop vs closed-loop control systems

• PID control (Proportional, Integral, Derivative)

• Feedback systems with sensors

• Autonomous movement and decision-making

• Safety systems in robotic operation

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Module 6: Artificial Intelligence in Robotics

• Introduction to AI in robotics: machine learning, computer vision, NLP

• Image recognition and object detection using cameras

• Path planning and obstacle avoidance

• Human-robot interaction concepts

• Autonomous robots in real-world scenarios

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Module 7: Robotics Project & Design Challenge

• Students design, build, and program a fully functional robot

• Integrate mechanical, electronic, and software components

• Test and optimize performance

• Present a project demonstration and technical report

• Optional: Compete in mini robotics challenges or competitions

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Module 8: Career Pathways and Ethics

• Careers in robotics: engineering, research, AI, mechatronics

• Emerging trends in robotics and automation

• Ethical considerations: AI safety, job displacement, and responsible robotics

• Teamwork, project management, and communication skills

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Skills Gained

• Mechatronics and hardware design

• Programming and algorithm development

• Problem-solving and analytical thinking

• Collaboration and project management

• Robotics troubleshooting and debugging

Week-by-Week Schedule

Course Duration: 16 weeks (can be extended to 18–20 weeks for more lab time)
Format: Lecture + Hands-On Lab + Project Work + Assessments

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Weeks 1–2: Module 1 – Introduction to Robotics

• Lecture Topics:

  • Definition and characteristics of robots

  • History and evolution of robotics

  • Types of robots and applications

  • Basic robotics terminology

• Hands-On Lab:

  • Explore a simple robotics kit (identify sensors, motors, microcontrollers)

  • Observe simple robot behaviors (line following or obstacle detection)

• Assignment: Short essay on “Robots in Daily Life”

• Assessment: Quiz on terminology, robot types, and applications

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Weeks 3–5: Module 2 – Mechanical Design & Kinematics

• Lecture Topics:

  • Robot structures and chassis types

  • Degrees of freedom (DOF)

  • Forward and inverse kinematics

  • End-effectors and grippers

  • Motors and actuators

• Hands-On Lab:

  • Build a simple robotic arm or wheeled robot

  • Test grippers and calculate DOF

• Assignment: Draw robot schematic and kinematics calculation

• Assessment: Practical test on building and moving a simple robot

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Weeks 6–8: Module 3 – Electronics & Sensors

• Lecture Topics:

  • Basic circuits, voltage, current, and power supply

  • Microcontrollers: Arduino/Raspberry Pi

  • Motors and actuators (DC, servo, stepper)

  • Sensors (ultrasonic, IR, gyroscope, accelerometer, touch)

  • Safety practices

• Hands-On Lab:

  • Connect sensors to Arduino and read data

  • Build a simple obstacle-avoiding robot

• Assignment: Sensor data logging and actuator response exercise

• Assessment: Lab demonstration of sensor-actuator integration

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Weeks 9–11: Module 4 – Programming for Robotics

• Lecture Topics:

  • Basics of programming (Python, C++, Arduino IDE)

  • Loops, conditionals, functions

  • Control logic and algorithms

  • Motion planning and navigation

  • Introduction to AI in robotics

• Hands-On Lab:

  • Program a line-following or obstacle-avoiding robot

  • Integrate sensors and motors for autonomous behavior

  • Mini AI project (optional: object detection or pattern recognition)

• Assignment: Write a program to control robot behavior

• Assessment: Practical programming test + quiz on algorithms

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Weeks 12–13: Module 5 – Control Systems & Automation

• Lecture Topics:

  • Open-loop vs closed-loop control

  • Feedback systems with sensors

  • PID control (P, I, D terms)

  • Automation examples in industry and robotics

• Hands-On Lab:

  • Implement PID control for a line-following robot

  • Build a simple automated pick-and-place or motion system

• Assignment: PID tuning report

• Assessment: Lab demonstration + short quiz on control systems

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Weeks 14–15: Module 6 – Artificial Intelligence in Robotics

• Lecture Topics:

  • Introduction to AI and machine learning in robotics

  • Computer vision basics

  • Path planning and navigation algorithms

  • Human-robot interaction and ethics

• Hands-On Lab:

  • Train a simple AI model (object/color recognition)

  • Program robot to navigate a maze using sensor data

• Assignment: AI project report (object detection or navigation)

• Assessment: Lab demonstration + quiz on AI concepts

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Weeks 16–19: Module 7 – Robotics Project & Design Challenge

• Project Work:

  • Brainstorm project ideas and create a proposal

  • Build and assemble the robot

  • Program autonomous or semi-autonomous behavior

  • Test and optimize performance

  • Prepare presentation and technical report

• Assessment:

  • Project demonstration (robot functionality and innovation)

  • Technical report evaluation

  • Peer and instructor feedback

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Weeks 20: Module 8 – Career Pathways and Ethics

• Lecture Topics:

  • Robotics and AI career opportunities

  • Emerging trends in robotics

  • Ethics, safety, and social impact

  • Soft skills for robotics professionals

• Activity:

  • Research and present a robotics-related career

  • Debate ethical dilemmas in AI and robotics

• Assessment: Participation + career roadmap submission

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Assessment Overview

• Quizzes: 10–15%

• Assignments & Reports: 20–25%

• Labs & Hands-On Exercises: 20–25%

• Final Project & Presentation: 30–35%