Glossary

1.3 Components of robotic systems

3 min read•july 25, 2024

Robotic systems rely on a combination of hardware and software components to function effectively. From sensors and actuators to controllers and end effectors, each part plays a crucial role in enabling robots to perceive, process, and interact with their environment.

Software is the brain behind robotic operations, encompassing control algorithms, programming languages, and frameworks like ROS. Sensors are the robot's eyes and ears, gathering data about the world around them. Together, these elements form the foundation of modern robotics.

Hardware Components of Robotic Systems

Hardware components of robotic systems

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  • Sensors gather environmental information convert physical phenomena into electrical signals provide input for decision-making and control (cameras, microphones)

  • Actuators convert energy into mechanical motion enable physical movement and manipulation (motors, pneumatic cylinders, hydraulic pistons)

  • Controllers interpret data and control actuators serve as central processing units (microcontrollers, single-board computers, industrial PLCs)

  • Power supply provides electrical energy to all components (batteries, power adapters, industrial power sources)

  • End effectors specialized tools attached to robot's arm or manipulator designed for specific tasks (grippers, welding torches, paint sprayers)

  • Structural components form robot's body using various materials (metals, plastics, composites)

Software and Sensing in Robotics

Software in robotic systems

  • Control algorithms determine robot behavior and decision-making processes (motion planning, trajectory generation, obstacle avoidance)

  • Programming languages used to write and implement robotic software (C++, Python, ROS-specific languages)

  • (ROS) open-source framework provides libraries tools and conventions for robotic applications

  • and AI enable robots to learn and adapt (neural networks, reinforcement learning)

  • (HRI) interfaces facilitate communication between humans and robots (voice commands, gesture recognition, graphical user interfaces)

  • Simulation software tests and develops robotic systems in virtual environments (Gazebo, V-REP, MATLAB Robotics Toolbox)

Common sensors in robotics

  • Encoders measure position speed and direction of motors or moving parts (optical, magnetic, absolute encoders)

  • Vision systems enable visual perception for object recognition tracking and navigation (2D cameras, stereo vision, depth sensors)

  • Force/torque sensors measure applied forces and moments crucial for precise control (assembly, manipulation, compliance control)

  • Inertial Measurement Units (IMUs) combine accelerometers and gyroscopes measure acceleration orientation and angular velocity

  • Proximity sensors detect nearby objects without physical contact (infrared, ultrasonic, capacitive sensors)

  • and localization systems provide positioning information (outdoor GPS, indoor beacon-based systems, SLAM techniques)

Principles of robotic actuators

  • Electric motors convert electrical energy into rotational mechanical energy (DC motors, stepper motors, servo motors)

  • Pneumatic systems use compressed air to create motion include air compressor valves and cylinders offer clean operation and low maintenance

  • Hydraulic systems utilize pressurized fluids to generate force and motion include pump reservoir valves and cylinders provide high power-to-weight ratio and smooth operation

  • Linear actuators convert rotational motion to linear motion (lead screws, ball screws, rack-and-pinion systems)

  • Piezoelectric actuators use materials that change shape when voltage applied provide precise small-scale movements

  • Shape memory alloys (SMAs) remember original shape when heated used for compact lightweight actuation in specific applications

Key Terms to Review (26)

Actuator: An actuator is a crucial component in robotic systems that converts energy, typically electrical or hydraulic, into physical motion. It plays a vital role in enabling robots to perform tasks by moving parts like joints or limbs. Actuators are responsible for providing the necessary force and motion, allowing robots to interact with their environment effectively and execute complex movements.
Algorithm: An algorithm is a step-by-step procedure or formula for solving a problem or completing a task. It serves as the backbone of robotic systems, guiding the decision-making processes and actions of robots by outlining clear instructions. Algorithms can range from simple sequences of commands to complex sets of rules, determining how robots perceive their environment and respond accordingly.
Artificial intelligence: Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning, reasoning, problem-solving, perception, and language understanding. AI plays a vital role in robotics, influencing the historical development of automated systems, contributing to the essential components of robotic architectures, and enhancing the functionality and applications of various types of robots.
Control System: A control system is a set of devices or algorithms that manage, command, direct, or regulate the behavior of other devices or systems. In robotics, control systems play a crucial role in ensuring that the robotic components operate in a coordinated manner to achieve desired outcomes. This involves feedback mechanisms that monitor the system's performance and adjust actions based on real-time data, allowing for precise movement and task execution.
Encoder: An encoder is a device that converts information from one format to another, often used to translate the position or motion of a robotic component into a digital signal. In robotics, encoders provide critical feedback on the movement of motors and joints, allowing for precise control and navigation. They are essential for ensuring that robots operate accurately according to their programmed tasks.
Feedback Loop: A feedback loop is a process in which the output of a system is circled back and used as input, allowing for continuous monitoring and adjustment. This dynamic interaction helps systems respond to changes in their environment, making them more adaptive and efficient. Feedback loops are crucial in robotic systems as they facilitate real-time adjustments, ensuring that robots can maintain desired performance despite variations in external conditions.
Force/torque sensor: A force/torque sensor is a device that measures the force and torque applied to an object, providing essential feedback for controlling robotic systems. These sensors allow robots to interact safely and effectively with their environment by detecting changes in force or torque, which can inform adjustments in movement or grip. This capability is crucial for tasks like assembly, manipulation, and ensuring safety during operations.
GPS: GPS, or Global Positioning System, is a satellite-based navigation system that allows users to determine their exact location (latitude, longitude, and altitude) anywhere on Earth. This technology plays a crucial role in robotic systems by providing accurate positional data, which is essential for navigation, mapping, and various autonomous tasks. The integration of GPS enhances both proprioceptive and exteroceptive sensing capabilities in robots and is fundamental in the context of sensor fusion and data processing.
Human-Robot Interaction: Human-robot interaction refers to the interdisciplinary field focused on the interactions between humans and robots, exploring how robots can effectively communicate, assist, and work alongside people. This area encompasses various aspects including the design, implementation, and evaluation of robotic systems that are intuitive and user-friendly for human users. Understanding these interactions is crucial for improving robotic functionality, ensuring safety, and fostering positive social impacts.
Hydraulic System: A hydraulic system is a technology that uses incompressible fluid to transmit force and perform work through the manipulation of pressure. This system is fundamental in robotics as it allows for powerful movements and precise control of robotic limbs, enabling machines to lift heavy loads or perform intricate tasks with relative ease. By harnessing the principles of fluid dynamics, hydraulic systems are integral components in many robotic applications, from industrial robots to advanced humanoid systems.
Industrial robot: An industrial robot is a programmable machine designed to carry out a variety of tasks in manufacturing and production environments, often performing repetitive actions with high precision and speed. These robots are integral to automating processes such as assembly, welding, painting, and material handling, leading to increased efficiency and safety in the workplace.
Inertial Measurement Unit: An inertial measurement unit (IMU) is a device that combines multiple sensors, typically accelerometers and gyroscopes, to measure and report a body's specific force, angular velocity, and sometimes magnetic field orientation. IMUs play a crucial role in robotic systems by providing essential data for navigation and control, allowing robots to understand their movement and orientation in three-dimensional space.
Linear Actuator: A linear actuator is a device that creates motion in a straight line, converting rotational motion into linear movement. This mechanism is crucial in robotics as it enables precise control over the position and movement of components within robotic systems. They can be powered by electric motors, pneumatic systems, or hydraulic pressure, offering versatility for various applications in automation and robotic manipulation.
Machine Learning: Machine learning is a subset of artificial intelligence that enables systems to learn from data and improve their performance over time without being explicitly programmed. It plays a critical role in the development and evolution of robotics by allowing machines to adapt their behaviors, recognize patterns, and make decisions based on past experiences. The integration of machine learning in robotic systems enhances their capabilities, enabling them to perform a variety of tasks, from industrial automation to human-robot collaboration.
Mobile robot: A mobile robot is a type of robotic system that is capable of moving around in its environment, performing tasks without being fixed to one location. These robots can navigate through various terrains and often utilize sensors and software to interact with their surroundings, making them suitable for a wide range of applications. Their mobility allows them to transport objects, gather data, and even assist in human activities across different settings.
Performance Metrics: Performance metrics are quantifiable measures used to evaluate the effectiveness and efficiency of a system or process. They play a crucial role in assessing how well robotic systems achieve their intended objectives, ensuring that designs and algorithms meet user requirements. By utilizing these metrics, developers can identify strengths and weaknesses in their systems, informing improvements and optimizations for better functionality and reliability.
Piezoelectric Actuator: A piezoelectric actuator is a device that converts electrical energy into mechanical motion using the piezoelectric effect, where certain materials change shape when an electric field is applied. This transformation allows for precise control of movement, making piezoelectric actuators essential components in robotics for applications requiring high accuracy and rapid response. They are often employed in areas like positioning systems, vibration control, and micro-manipulation in robotic systems.
Pneumatic System: A pneumatic system is a technology that uses compressed air to transmit and control energy. These systems are often used in robotics to facilitate movement and operation of various components, such as actuators and valves, leveraging the force of compressed air to perform work efficiently and effectively. By utilizing pneumatic power, robotic systems can achieve rapid movements and precise control, making them ideal for applications requiring agility and responsiveness.
Robot Operating System: Robot Operating System (ROS) is an open-source framework that provides a collection of software libraries and tools to help develop robotic applications. It serves as a middleware, enabling communication between different components of a robotic system and simplifying the development process for robotic algorithms and applications. With its modular architecture, ROS allows developers to build, simulate, and control robots more efficiently by reusing code and integrating various sensors and actuators seamlessly.
Robotic programming language: A robotic programming language is a specialized coding language designed for controlling and programming robots, enabling them to perform specific tasks. These languages provide the syntax and structure necessary for defining robot behaviors, manipulating sensor data, and controlling actuators, facilitating effective interaction between software and hardware components of robotic systems.
Rodney Brooks: Rodney Brooks is a prominent roboticist and entrepreneur known for his work in artificial intelligence and robotics, particularly in the development of behavior-based robotics. His contributions have significantly influenced the field, leading to the creation of various robots that interact with their environment in a more human-like manner, revolutionizing the design and functionality of robotic systems.
Sensor: A sensor is a device that detects and responds to physical stimuli from the environment, such as light, temperature, motion, or pressure. In robotic systems, sensors play a crucial role by providing the necessary data for decision-making and enabling robots to interact with their surroundings effectively. They are essential components that allow robots to perceive their environment, facilitating tasks like navigation, object recognition, and environmental monitoring.
Shape Memory Alloy: A shape memory alloy (SMA) is a type of material that can return to a predetermined shape when heated after being deformed. This unique property makes SMAs particularly useful in robotics, where they can act as actuators or sensors, providing movement or responsiveness without complex mechanical systems. Their ability to change shape in response to temperature changes enables innovative designs and applications in various robotic components.
Sherry Turkle: Sherry Turkle is a sociologist and psychologist renowned for her research on the impact of technology on human relationships and communication. Her work emphasizes how digital interactions, particularly through robotics and artificial intelligence, shape our understanding of connection, intimacy, and identity, highlighting both the benefits and challenges of integrating robots into society.
System Integration: System integration refers to the process of combining various subsystems or components into a unified whole that functions cohesively. In robotics, this involves ensuring that different parts like sensors, actuators, and control systems work together efficiently to achieve the desired performance of the robotic system. The effectiveness of system integration is crucial for the seamless operation of robotic applications, as it directly impacts the overall functionality and reliability of the robot.
Vision System: A vision system is a technology that enables a robot to interpret visual information from its environment using cameras and image processing algorithms. This allows the robot to understand its surroundings, identify objects, and make decisions based on visual data. Vision systems are crucial for tasks like navigation, manipulation, and inspection, making them a key component in robotic systems.
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