Robotics Programs and Software

• Programs are sets of instructions that operate on an input to produce an output.
• Robots use computer programs executed on a processor to process sensor data, perform cognition, and plan actions.

Face Recognition Program Example

• Takes an image as input
• Scans the image for specific features
• Compares image features to a library of known faces
• Finds a match
• Returns the name of the person as an output

Programming Languages

• Many programming languages are available, including C/C++, Java, Fortran, and Python
• C/C++ is the most popular language in robotics
• C++ is an object-oriented successor to the C language
• Python is also popular for machine learning and can be used to develop ROS (Robot Operating System) packages.

Software Tools in Robotics

• Robot Operating System (ROS) is a set of software libraries and tools for building robot applications.
• Programs for ROS can be written in C/C++ or Python
• Matlab interfaces with ROS and is used for data analysis
• Octave is a free, open-source equivalent to Matlab

C Programming and Arduino

• C/C++ is widely used for programming robots
• The Arduino microcontroller employs a programming language based on C
• Using the Arduino microcontroller is a good way to learn the basics of C while working on hands-on robotics projects

Robot Programming

• Robot programming involves providing instructions to a robot
• Instructions enable robots to perform specific tasks
• Tasks are performed under teleoperation, full autonomy, or semi-autonomy.
• Instructions are written in a programming language that the robot can understand and execute

Reasons to Learn Robot Programming

• Robot programming provides many possibilities to automate tasks in various industries.
• Skills are highly sought after in robotics, automation, and artificial intelligence.
• Robot programming challenges problem-solving skills, figuring out how to make a machine interact effectively with its environment.

Choosing a Robot

• Key considerations when choosing a robot include budget, task requirements, programming experience, expandability, and operating system compatibility
• Additional considerations include community and support and safety features

Core Principles

• Sensing and Perception: Robots employ a variety of sensors
  • Cameras
  • Lidar
  • Ultrasonic sensors
  • Light sensors
  • Gesture touch sensors
  • Motion sensors
• Data Processing: Collected sensor data must be processed to extract usable information
  • Image processing for camera data
  • Filtering algorithms for noisy sensor readings
• Sensor Fusion: Advanced robots combine data from multiple sensors to create a more comprehensive view of the environment
• Machine Learning: Neural networks can teach robots to recognize objects and patterns and make predictions based on sensor data

Decision-Making Algorithms

• Robots vacuum uses a simple algorithm to avoid obstacles
• Self-driving car relies on AI algorithms for navigation and collision avoidance
• Path Planning: Algorithms to helps robots find the most efficient route between locations while avoiding obstacles
• Reactive systems react quickly to immediate sensor input
• Deliberative systems plan actions more strategically
• Learning-Based Decision Making: Decision-making can adapt based on previous interactions and data collected from sensors

Actuators and Motion Control

• Robots uses various actuators, including motors, servos, and pneumatic systems
  • Motors provide precise movement control.
  • Pneumatic actuators offer rapid force generation
• Kinematics: The study of how robots move
  • Forward and inverse kinematics determine how joint angles affect the robot's end-effector
• Motion Control: Algorithms dictate how actuators should move to achieve desired movements
• Feedback systems monitor position and orientation
  • Encoders and gyroscopes are feedback systems
  • Feedback ensures accurate motion control.