Robotics 2: Grade 11 Advanced Curriculum
Prerequisite: Robotics 1 (or equivalent understanding of basic robotics principles, mechanics, sensors,
and programming)
Course Goal: To deepen students' understanding of robotics by exploring more advanced concepts in
mechanical design, programming, sensor integration, control systems, and autonomous behavior,
culminating in a complex, student-driven project.
Target Audience: Grade 11 Students
Suggested Platforms/Kits: Continue with platforms from Robotics 1 (LEGO Mindstorms, VEX, Arduino-
based kits), potentially introducing more advanced sensors, microcontrollers (e.g., Raspberry Pi for
vision/AI), or more complex mechanical components.
Module 1: Advanced Mechanical Design & Fabrication (5-7 Weeks)
1.1 Review of Robotics 1 Mechanics: Gears, levers, basic chassis design.
1.2 Advanced Drivetrains:
o Holonomic drives (e.g., mecanum wheels, omni-wheels) - design and control
implications.
o Suspension systems for varied terrain.
o Efficiency and power transmission optimization.
1.3 Multi-Degree-of-Freedom Manipulators:
o Designing arms with 3+ degrees of freedom (DOF).
o Introduction to kinematic concepts (forward kinematics intuitively).
o Linkages and complex mechanisms (e.g., scissor lifts, parallel grippers).
1.4 Introduction to CAD (Computer-Aided Design):
o Basics of a simple CAD tool (e.g., Tinkercad, Onshape for Education, Fusion 360 -
introductory level).
o Designing custom parts for robots.
1.5 Introduction to Digital Fabrication (Optional, based on resources):
o 3D printing basics: from CAD model to physical part.
o Laser cutting basics for structural components.
Project 1: The Advanced Manipulator Challenge
o Design and build a robot with a multi-DOF arm to perform a complex manipulation task
(e.g., stacking objects in a specific sequence, navigating an object through a tight space).
o Option to design and fabricate a custom part if CAD/fabrication is covered.
Module 2: Intermediate Programming for Robotics (6-8 Weeks)
2.1 Transitioning to/Deepening Text-Based Programming:
o If using block-based in Robotics 1, transition to Python or C++.
o If already using text-based, delve deeper into syntax and structure.
o Variables, data types (integers, floats, strings, booleans, arrays/lists).
o Control flow: advanced loops (for, while), nested conditionals.
2.2 Functions and Modularity:
o Writing custom functions to organize code and promote reusability.
o Parameters and return values.
o Breaking down complex tasks into smaller, manageable functions.
2.3 Introduction to Data Structures:
o Arrays/Lists for storing collections of sensor data or waypoints.
o Simple data organization techniques.
2.4 Basic Algorithms for Robotics:
o Search algorithms (e.g., simple sequential search).
o Sorting algorithms (e.g., bubble sort - conceptual).
o Applying algorithms to robot decision-making (e.g., finding the closest object).
2.5 Debugging Techniques:
o Systematic approaches to finding and fixing errors in code.
o Using print statements or debugger tools effectively.
Project 2: The Algorithmic Robot
o Program a robot to perform a task that requires more complex logic, data storage, and
custom functions.
o Examples: A robot that sorts objects by color, a robot that follows a complex path
defined by a list of waypoints, a robot that searches an area for multiple items.
Module 3: Advanced Sensing & Data Processing (6-8 Weeks)
3.1 Sensor Review and Calibration:
o Importance of sensor accuracy and calibration techniques.
3.2 Working with Analog and Digital Signals:
o Understanding the difference and how microcontrollers process them.
3.3 Advanced Sensor Integration:
o Encoders for precise motor control and odometry (distance/position tracking).
o Inertial Measurement Units (IMUs): Accelerometers, gyroscopes, magnetometers for
orientation and motion tracking.
o Introduction to GPS (if applicable and resources allow).
3.4 Introduction to Computer Vision (Conceptual & Basic Implementation):
o Using a camera as a sensor (e.g., PixyCam, webcam with Raspberry Pi).
o Basic concepts: color detection, blob detection, object tracking.
o Thresholding and simple image filtering.
3.5 Basic Sensor Fusion:
o Concept of combining data from multiple sensors for a more robust understanding of
the environment (e.g., using ultrasonic and encoders for better obstacle avoidance and
localization).
Project 3: The "Seeing" Robot
o Develop a robot that uses advanced sensors or basic computer vision to perform a task.
o Examples: A robot that navigates using IMU data, a robot that tracks and follows a
colored object using a camera, a robot that uses odometry to map a small area.
Module 4: Introduction to Control Systems & Autonomous Behavior (5-7 Weeks)
4.1 Feedback Control Revisited:
o Deeper dive into PID (Proportional-Integral-Derivative) control:
Tuning PID controllers for optimal performance (e.g., for motor speed, line
following, arm positioning).
Practical implementation and experimentation.
4.2 State Machines for Complex Behaviors:
o Designing more sophisticated state machines to manage complex robot tasks and
transitions.
4.3 Basic Path Planning and Navigation Algorithms:
o Introduction to concepts like A* (A-star) or Dijkstra's algorithm (conceptual, or simplified
implementation).
o Bug algorithms (e.g., Tangent Bug) for obstacle avoidance.
4.4 Introduction to Localization:
o "Where am I?" - Basic concepts of how robots determine their position in an
environment (e.g., using odometry, landmarks).
4.5 Decision Making Under Uncertainty (Conceptual):
o How robots can make decisions when sensor data is noisy or incomplete.
Project 4: The Autonomous Explorer
o Design and program a robot to autonomously navigate a more complex environment,
possibly with unknown elements.
o Examples: A robot that explores a maze and finds the exit, a robot that maps an area by
identifying key features, a robot that performs a delivery task to a specified location
while avoiding dynamic obstacles.
Module 5: Human-Robot Interaction (HRI) & Ethics (2-3 Weeks)
5.1 Principles of Human-Robot Interaction:
o How humans and robots can work together effectively and safely.
o Designing intuitive interfaces for controlling or interacting with robots.
o Robot expression and communication (e.g., lights, sounds, simple displays).
5.2 Advanced Ethical Discussions:
o Autonomous weapons, AI bias in robotics, job displacement due to advanced
automation.
o The role of robotics in solving global challenges (e.g., climate change, healthcare).
5.3 Designing for User Experience (UX) in Robotics:
o Considering the end-user when designing robotic systems.
Activity/Mini-Project: Design an HRI Scenario
o Students design and prototype (e.g., through storyboards, simple simulations, or role-
playing) an interaction between a human and a robot for a specific task, focusing on
clarity, safety, and effectiveness.
Module 6: Capstone Project (6-8 Weeks)
6.1 Project Definition and Proposal:
o Students work in teams to define a significant robotics problem they want to solve or a
complex task they want their robot to achieve.
o Develop a project proposal outlining goals, design, required components, and timeline.
6.2 Design, Build, Program, Test, Iterate:
o Students apply knowledge and skills from Robotics 1 and 2.
o Emphasis on the engineering design process: iterative development, testing, and
refinement.
o Regular progress checks and mentorship.
6.3 Documentation and Presentation:
o Documenting their design, code, challenges, and solutions.
o Preparing a final presentation and demonstration of their capstone project to peers,
teachers, and potentially a wider audience.
Possible Capstone Project Themes:
o Search and rescue robot for a simulated disaster zone.
o Automated greenhouse assistant.
o Interactive robotic game player.
o Art-creating robot.
o Warehouse automation task (e.g., sorting and delivering packages).
Assessment:
Functionality, complexity, and innovation of projects.
Quality of code, mechanical design, and system integration.
Problem-solving skills and iterative design process.
Individual contributions to team projects.
Technical documentation and project proposals.
Final capstone project demonstration and presentation.
Quizzes or exams on advanced concepts.
Differentiation:
Capstone projects can vary in complexity based on student skill levels.
Provide access to more advanced tools/software for highly motivated students.
Offer specialized workshops or tutorials on specific advanced topics (e.g., machine learning
basics with Raspberry Pi, advanced CAD).
This Robotics 2 curriculum aims to challenge students further, encouraging them to think critically, solve
complex problems, and innovate. The capstone project provides a significant opportunity for them to
synthesize their learning and create something truly impressive.
