Robotics and Autonomous Systems

Robotics and Autonomous Systems is an interdisciplinary field that integrates computer science, artificial intelligence, and engineering to design and operate intelligent machines that can perform tasks without direct human control. It focuses on developing the core computational components that enable a system to perceive its environment through sensors, plan a course of action to achieve a goal, and control its physical actuators to execute that plan. This involves the study and application of topics like computer vision, machine learning, sensor fusion, and motion planning to build sophisticated systems—such as self-driving cars, unmanned drones, and planetary rovers—that can function reliably and safely in complex, dynamic worlds.

1. Introduction to Robotics and Autonomous Systems
   1. Defining Robotics
      1. Essential Characteristics of Robots
      2. Distinction Between Robots and Automated Machines
      3. Levels of Autonomy
         1. Manual Control
         2. Assisted Control
         3. Supervised Autonomy
         4. Full Autonomy
   2. Historical Development
      1. Early Automata and Mechanical Devices
      2. Industrial Revolution Impact
      3. First Industrial Robots
      4. Modern Robotics Era
      5. AI Integration Timeline
      6. Key Milestones in Autonomous Systems
   3. Robot Classification Systems
      1. Classification by Application Domain
         1. Industrial Robots
         2. Medical Robots
         3. Service Robots
         4. Exploration Robots
         5. Military and Defense Robots
         6. Entertainment Robots
         7. Agricultural Robots
      2. Classification by Locomotion Method
         1. Wheeled Robots
            1. Differential Drive
            2. Ackermann Steering
            3. Omnidirectional Wheels
         2. Legged Robots
            1. Bipedal Robots
            2. Quadrupedal Robots
            3. Hexapods
            4. Multi-legged Systems
         3. Aerial Robots
            1. Fixed-wing Aircraft
            2. Multirotor Systems
            3. Hybrid VTOL
         4. Underwater Robots
            1. Remotely Operated Vehicles
            2. Autonomous Underwater Vehicles
         5. Hybrid Locomotion Systems
      3. Classification by Mechanical Architecture
         1. Manipulator Robots
         2. Mobile Robots
         3. Humanoid Robots
         4. Swarm Robotics Systems
   4. Fundamental System Architecture
      1. Sense-Plan-Act Paradigm
         1. Sensing Phase
         2. Planning Phase
         3. Acting Phase
         4. Feedback Integration
      2. Hardware Components
         1. Sensor Systems
         2. Actuator Systems
         3. Processing Units
         4. Power Management
         5. Communication Interfaces
      3. Software Architecture
         1. Operating System Layer
         2. Middleware Layer
         3. Control Software
         4. Perception Modules
         5. Planning Modules
   5. Mathematical Prerequisites
      1. Linear Algebra Foundations
         1. Vector Operations
         2. Matrix Operations
         3. Transformations
         4. Eigenvalues and Eigenvectors
      2. Rotation Mathematics
         1. 2D Rotations
         2. 3D Rotations
         3. Rotation Composition
      3. Probability Theory
         1. Probability Distributions
         2. Bayes' Theorem
         3. Gaussian Models
         4. Uncertainty Representation
      4. Calculus Applications
         1. Derivatives in Motion
         2. Integrals in Control
         3. Differential Equations
         4. Optimization Theory