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Robotics Glossary

Understand the terminology and concepts behind humanoid robotics. From basic mechanics to advanced AI, learn the language of the future.

Showing 32 of 32 terms

A

Actuator

A mechanical component that converts energy into motion, enabling a robot to move its joints and limbs.

Actuators are the "muscles" of a robot. They can be electric motors, hydraulic cylinders, or pneumatic devices that create controlled movement in response to control signals.

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AI (Artificial Intelligence)

Computer systems that can perform tasks typically requiring human intelligence, such as visual perception, speech recognition, and decision-making.

In humanoid robots, AI enables autonomous behavior, learning from experience, natural language processing, and adaptive responses to changing environments.

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Autonomous

Operating independently without human control or intervention.

Autonomous robots can perceive their environment, make decisions, and execute actions without constant human guidance, though they may still operate within defined parameters.

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B

Bipedal

Walking or moving on two legs.

Bipedal locomotion is a key challenge in humanoid robotics, requiring sophisticated balance systems, sensors, and control algorithms to maintain stability while walking.

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C

Center of Mass (COM)

The point where the total mass of a robot can be considered to be concentrated.

Understanding and controlling the center of mass is crucial for maintaining balance in humanoid robots, especially during dynamic movements like walking or reaching.

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Computer Vision

Technology that enables robots to derive meaningful information from digital images or videos.

Computer vision allows humanoid robots to identify objects, navigate spaces, recognize faces, read text, and understand their visual environment in real-time.

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D

DOF (Degrees of Freedom)

The number of independent ways a robot or robot joint can move.

A human arm has 7 DOF (shoulder: 3, elbow: 1, wrist: 3). More DOF generally means more flexibility and dexterity, but also more complexity in control.

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E

End Effector

The device at the end of a robotic arm designed to interact with the environment.

End effectors include grippers, hands, tools, or sensors. In humanoid robots, these are often multi-fingered hands capable of complex manipulation tasks.

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G

Gait

The pattern of movement during locomotion.

Humanoid robots must develop stable gaits for walking, running, or climbing stairs. Different gaits optimize for speed, stability, or energy efficiency.

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Gyroscope

A sensor that measures angular velocity and orientation.

Gyroscopes help humanoid robots maintain balance by detecting tilting or rotation, allowing the control system to make rapid corrections.

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H

Haptic Feedback

Technology that creates tactile sensations, providing a sense of touch.

Haptic sensors in robot hands allow them to feel pressure, texture, and temperature, enabling delicate manipulation of objects without damaging them.

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I

IMU (Inertial Measurement Unit)

A sensor that measures acceleration, angular velocity, and sometimes magnetic field.

IMUs are essential for humanoid robot balance and navigation, providing real-time data about the robot's orientation and movement in 3D space.

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Inverse Kinematics

Mathematical process of calculating joint angles needed to achieve a desired end-effector position.

When a robot needs to reach a specific point in space, inverse kinematics determines how each joint must move to get there, solving complex geometric problems.

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J

Joint

A connection point between two rigid parts that allows relative motion.

Robot joints mimic biological joints like elbows, knees, and shoulders. They can be revolute (rotating), prismatic (sliding), or more complex types.

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L

LiDAR (Light Detection and Ranging)

A sensing method that uses laser pulses to measure distances and create 3D maps of the environment.

LiDAR enables robots to build detailed spatial maps, detect obstacles, and navigate complex environments with high precision, even in low light.

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Localization

The process of determining a robot's position within its environment.

Accurate localization is crucial for navigation. Robots use various sensors (cameras, LiDAR, IMU) and algorithms to track their position relative to a map or landmarks.

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M

Machine Learning

A subset of AI where systems learn and improve from experience without explicit programming.

Machine learning enables robots to recognize patterns, adapt to new situations, and improve performance over time through training on large datasets.

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Manipulation

The ability to physically interact with and control objects in the environment.

Manipulation tasks range from grasping and placing objects to using tools, requiring coordination of vision, touch sensors, and motor control.

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Motion Planning

The computational process of finding a path for a robot to move from one configuration to another.

Motion planning algorithms must avoid obstacles, maintain balance, and optimize for factors like speed, energy efficiency, or smoothness of movement.

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N

Natural Language Processing (NLP)

AI technology that enables robots to understand and respond to human language.

NLP allows humanoid robots to have conversations, follow verbal commands, and communicate naturally with humans using speech recognition and generation.

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O

Odometry

Using sensor data to estimate change in position over time.

Wheel odometry tracks rotations to estimate distance traveled. Visual odometry uses camera images. Both help robots track their movement between position updates.

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P

Path Planning

Finding a collision-free route from a starting point to a goal location.

Path planning algorithms like A* or RRT compute efficient routes while avoiding obstacles, considering robot dimensions, and optimizing for various constraints.

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Payload

The maximum weight a robot can carry or manipulate effectively.

Payload capacity is a key specification for humanoid robots, determining what tasks they can perform, from carrying boxes to operating tools.

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PID Controller

A control algorithm that adjusts outputs based on Proportional, Integral, and Derivative calculations.

PID controllers are fundamental in robotics for maintaining desired positions, velocities, or forces by continuously correcting for errors.

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R

ROS (Robot Operating System)

An open-source framework providing tools and libraries for robot software development.

ROS is widely used in robotics research and development, offering standardized ways to handle sensors, actuators, communications, and control algorithms.

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S

Sensor Fusion

Combining data from multiple sensors to produce more accurate and reliable information.

By integrating data from cameras, IMUs, LiDAR, and other sensors, robots can overcome individual sensor limitations and build robust understanding of their environment.

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Servo

A motorized device that provides precise control of angular or linear position.

Servos are common in robot joints, offering accurate position control with feedback. They enable the precise movements needed for walking, reaching, and manipulation.

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SLAM (Simultaneous Localization and Mapping)

A technique for building a map of an unknown environment while tracking the robot's location within it.

SLAM is essential for autonomous navigation in new spaces, allowing robots to explore while creating spatial maps they can use for future navigation.

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T

Teleoperation

Remote control of a robot by a human operator.

Teleoperation allows humans to control robots from a distance, useful for dangerous environments, training, or tasks requiring human judgment.

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Torque

Rotational force that causes an object to rotate around an axis.

Joint torque determines how much force a robot can apply. Higher torque enables lifting heavier objects or moving more quickly, but requires more powerful actuators.

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Trajectory

The path that a robot or robot part follows through space over time.

Trajectory planning ensures smooth, controlled movement from start to goal, considering velocity, acceleration, and avoiding sudden jerky motions.

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Z

Zero Moment Point (ZMP)

A point on the ground where the net moment of forces is zero, used for balance in bipedal robots.

Keeping the ZMP within the support polygon (area of foot contact) is crucial for stable walking. ZMP-based control is a common approach for humanoid locomotion.

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