🤖Robotics Unit 1 – Introduction to Robotics and Robotic Systems

Key Concepts and Terminology

• Robotics involves the design, construction, operation, and application of robots
• Robots are machines capable of carrying out complex actions automatically
• Automation refers to the use of control systems and information technologies to reduce the need for human intervention
• Kinematics studies the motion of objects without considering the forces that cause the motion
• Actuators are components responsible for moving or controlling a mechanism or system
• Sensors allow robots to gather information about their environment and respond accordingly
• Control systems enable robots to perform desired tasks by regulating their behavior and movement
• Degrees of freedom (DOF) indicate the number of independent ways a robot can move through space

Historical Overview of Robotics

• The concept of automata, or self-operating machines, dates back to ancient civilizations (ancient Greece, China)
• In the 20th century, the development of computers and advancements in electronics laid the foundation for modern robotics
• The first industrial robot, Unimate, was introduced by George Devol and Joseph Engelberger in 1961
  • It was used for die casting and welding in General Motors factories
• NASA's Viking program (1975) and the Mars Pathfinder mission (1997) utilized robotic probes and rovers for space exploration
• The field of robotics has expanded rapidly since the 1980s with advancements in artificial intelligence, sensors, and computing power
• Collaborative robots (cobots) designed to work alongside humans gained popularity in the early 21st century

Types of Robots and Their Applications

• Industrial robots are used in manufacturing for tasks such as welding, painting, assembly, and material handling
  • They offer high precision, speed, and repeatability in production lines
• Service robots assist humans in various tasks, including household chores (vacuuming, lawn mowing), healthcare, and customer service
• Medical robots aid in surgical procedures, rehabilitation, and patient care
  • Examples include the da Vinci Surgical System and exoskeletons for physical therapy
• Autonomous vehicles, such as self-driving cars and drones, navigate their environment without human intervention
• Humanoid robots are designed to resemble human form and behavior, often used for research and social interaction
• Space robots, like the Mars rovers (Curiosity, Perseverance), explore and gather data in extraterrestrial environments

Components of Robotic Systems

• Mechanical structure provides support and determines the robot's shape and size
  • It includes the frame, linkages, and joints that enable motion
• Actuators, such as electric motors, hydraulic systems, and pneumatic systems, convert energy into motion
• Sensors gather data about the robot's environment and internal states
  • Examples include cameras, infrared sensors, and force/torque sensors
• Control systems process sensor data, make decisions, and send commands to actuators
  • They often involve microcontrollers, computers, and software algorithms
• Power supply provides the necessary energy for the robot to operate, which can be electrical, hydraulic, or pneumatic
• End effectors are the tools or devices attached to the robot's arm for interacting with the environment (grippers, welding torches)

Robotic Kinematics and Motion Planning

• Forward kinematics determines the position and orientation of the end effector based on the known joint angles and link lengths
  • It uses the Denavit-Hartenberg (DH) convention to describe the robot's geometry
• Inverse kinematics calculates the joint angles required to achieve a desired end effector position and orientation
  • It is more complex than forward kinematics and may have multiple solutions
• Motion planning involves generating a path for the robot to follow while avoiding obstacles and optimizing certain criteria (shortest path, minimal energy)
• Trajectory planning determines the speed and acceleration profiles for the robot's joints to follow the planned path smoothly
• Collision detection and avoidance algorithms ensure the robot does not collide with objects in its workspace

Sensors and Actuators in Robotics

• Encoders measure the angular position and velocity of robot joints, enabling precise control and feedback
• Force/torque sensors detect the forces and moments applied to the robot's end effector, crucial for tasks requiring physical interaction
• Vision systems, such as cameras and lidar, allow robots to perceive their environment and identify objects
  • They enable tasks like object recognition, tracking, and visual servoing
• Tactile sensors provide information about contact forces and surface properties, enhancing the robot's ability to manipulate objects
• Electric motors, the most common type of actuator, convert electrical energy into mechanical motion
  • They offer high precision, controllability, and efficiency
• Hydraulic and pneumatic actuators use pressurized fluids or gases to generate large forces and torques, suitable for heavy-duty applications

Programming and Control Systems

• Robot programming involves writing software instructions to define the robot's behavior and actions
• Low-level programming languages, such as C++ and Python, provide direct control over the robot's hardware and real-time performance
• High-level programming environments, like ROS (Robot Operating System), offer libraries and tools for rapid development and integration
• Teach pendants are handheld devices used for manual robot programming and control, commonly used in industrial settings
• Feedback control systems, such as PID (Proportional-Integral-Derivative) controllers, ensure the robot follows the desired trajectory accurately
• Machine learning and artificial intelligence techniques enable robots to learn from data, adapt to new situations, and make intelligent decisions

Current Trends and Future Directions

• Collaborative robots (cobots) are designed to work safely alongside humans in shared workspaces, opening up new possibilities for human-robot interaction
• Soft robotics focuses on creating robots with compliant and flexible materials, mimicking the properties of biological systems
  • It has applications in gripping delicate objects, wearable devices, and biomedical engineering
• Cloud robotics leverages the power of cloud computing to offload computation, share data, and enable robot-to-robot communication
• Swarm robotics involves the coordination and control of large numbers of simple robots to achieve complex behaviors and tasks
• Neuromorphic engineering aims to develop robot controllers and sensors inspired by the principles of biological neural networks
• Advances in artificial intelligence, particularly in deep learning and reinforcement learning, are enabling robots to learn complex skills and adapt to dynamic environments
• The integration of robotics with other emerging technologies, such as the Internet of Things (IoT) and 5G networks, is expected to create new opportunities and applications