Course Overview: Robotics 2
Welcome to Robotics 2, an advanced, project-driven course designed for students ready to move beyond basic automation into the realm of Intelligent Machines. This course shifts the focus from simple "act-and-react" programming to sophisticated systems that perceive, reason, and learn.
The semester culminates in the ambitious construction and programming of a Humanoid Robot, testing your skills in high-level integration and bio-inspired engineering.
Advanced Technical Modules
Design & Kinematics: Master the mathematics of motion. We will study Inverse Kinematics, allowing you to calculate the exact joint angles needed for a robot hand to reach a specific coordinate in 3D space.
Robot Dynamics: Beyond just motion, we study the forces behind it. Students will analyze torque, acceleration, and center of mass—critical for keeping a bipedal humanoid balanced.
Simulation & Digital Twins: Before touching hardware, you will build and test your designs in high-fidelity physics simulators. This allows for rapid prototyping and "crash-safe" experimentation.
Pendant Training & Learning: Explore how industrial robots "learn" through Lead-through Programming and Teach Pendants, mimicking the way professional technicians calibrate manufacturing arms.
Perception (Vision & Recognition): Give your robot eyes. Using Computer Vision (CV), students will program robots to identify shapes, track colors, and recognize specific objects or faces in real-time.
Communication & Interaction: We explore the "social" side of robotics, including Natural Language Processing (NLP) for speech recognition and synthesized voice response, allowing for human-robot dialogue.
The Capstone Project: The Humanoid Challenge
The core of Robotics 2 is the assembly and "nurturing" of a humanoid platform. This project integrates every topic covered in the curriculum:
Mechanical Assembly: Building a multi-jointed skeletal structure.
Sensory Integration: Wiring the "eyes" (cameras) and "ears" (microphones).
The AI Brain: Implementing Machine Learning algorithms so the robot can improve its performance through experience.
Autonomous Thinking: Transitioning from scripted paths to AI-driven decision-making, where the robot must navigate a room or perform a task without human intervention.