CSE461: Introduction to Robotics

Taught CSE461: Introduction to Robotics during Fall 2024. This course introduces the core computational, mechanical, and electronic foundations required to build and program autonomous robotic systems.

Pre-requisite: CSE360
Semester Taught: Fall 2024
Institution: BRAC University, Department of Computer Science and Engineering

Course Description

This course provides a comprehensive introduction to robotics, exploring mechanical structures, kinematics, sensor perception, actuator systems, feedback control, and autonomous decision-making. Students learn the mathematical formulation of spatial descriptions and homogeneous coordinate transformations, manipulator forward and inverse kinematics using Denavit-Hartenberg (D-H) parameters, differential kinematics, and trajectory planning. The course also addresses wheeled mobile robot kinematics, motor drive electronics, multi-sensor perception (ultrasonic, LiDAR, IMU, cameras), computer vision algorithms for robotic navigation, and hardware system integration.

Course Objectives

• Introduce core robotics laws, system architectures, coordinate frames, and control hierarchies.
• Develop rigorous mathematical formulations for spatial representations, homogeneous transformation matrices, and forward/inverse kinematics.
• Study actuation technologies, motor control circuits (H-bridges, PWM), and differential drive locomotion.
• Cover sensor perception, sensor fusion, computer vision algorithms, and environmental feature extraction.
• Guide student teams through the complete design, construction, and programming of an autonomous robotic system.

Course Topics & Outline

• Introduction to Robotics: Robotic classification, autonomy levels, work envelopes, and degree of freedom (DOF) analysis.
• Spatial Representations & Transformations: Translation, rotation matrices, Euler angles, and 4x4 homogeneous transformation matrices.
• Manipulator Kinematics: Forward kinematics using Denavit-Hartenberg (D-H) conventions, link parameters, and inverse kinematics solutions.
• Mobile Robotics & Locomotion: Differential drive kinematics, non-holonomic constraints, wheel odometry, and dead reckoning.
• Actuators & Motor Control: DC motors, stepper motors, servo motors, motor drivers, encoders, and PWM control.
• Robotic Sensing & Perception: Encoders, ultrasonic rangers, infrared sensors, Inertial Measurement Units (IMUs), and LiDAR.
• Robot Vision: Camera modeling, perspective projection, color segmentation, contour detection, and visual tracking.
• Control Systems: Open-loop vs. closed-loop control, Proportional-Integral-Derivative (PID) controllers, and error compensation.
• Path Planning & Navigation: Bug algorithms, potential fields, grid-based path planning (A* search), and obstacle avoidance.
• System Integration: End-to-end hardware prototyping and software control for autonomous robotic tasks.

Textbooks & Reference Materials

1. Springer Handbook of Robotics, Bruno Siciliano and Oussama Khatib (Eds.), 2nd Edition, Springer, ISBN: 9783319325507.
2. Robotics, Vision and Control: Fundamental Algorithms in MATLAB, Peter Corke, 2nd Edition, Springer, ISBN: 9783642201431.
3. Introduction to Robotics: Mechanics and Control, John J. Craig, 4th Edition, Pearson, ISBN: 9780133489798.
4. Departmental lecture slides, circuit schematics, datasheets, and robotics project guidelines provided via buX.