Scientific Glossary

Actuator

An actuator is a component that converts energy (electrical, hydraulic, or pneumatic) into mechanical motion. In robotics, actuators are the 'muscles' of a robot — they enable movement and physical interaction with the environment.

Degrees of Freedom (DOF)

Degrees of Freedom (DOF) refers to the number of independent parameters that define the configuration or motion of a robotic system. In 3D space, a rigid body has 6 DOF: 3 translational (X, Y, Z) and 3 rotational (roll, pitch, yaw). A robot's DOF determines the complexity of motions it can perform.

Inverse Kinematics (IK)

Inverse Kinematics (IK) is the mathematical process of determining the joint parameters (angles or displacements) required to place a robot's end-effector at a desired position and orientation in space. It is the inverse of forward kinematics, which calculates end-effector pose from known joint values.

LiDAR

LiDAR (Light Detection and Ranging) is a remote sensing technology that measures distances by emitting laser pulses and detecting the reflected light. In robotics, LiDAR sensors generate 2D or 3D point clouds of the surrounding environment, enabling obstacle detection, mapping, and localization.

P-value

The p-value is the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. A small p-value (typically ≤ 0.05) suggests strong evidence against the null hypothesis, leading researchers to reject it. It does not indicate the probability that the null hypothesis is true, nor the size of an effect.

Path Planning

Path planning (also called motion planning) is the process of computing a collision-free trajectory for a robot to move from a start configuration to a goal configuration. It considers the robot's geometry, joint limits, and the obstacles in its environment to find a feasible and often optimal path.

Reinforcement Learning (RL) in Robotics

Reinforcement Learning (RL) is a machine learning paradigm where an agent learns to make decisions by interacting with an environment, receiving rewards for desirable actions and penalties for undesirable ones. In robotics, RL enables robots to learn complex behaviors — such as locomotion, manipulation, and navigation — without explicit programming of every motion.

Robot

A robot is a programmable machine capable of carrying out a series of actions autonomously or semi-autonomously. Robots can be physical (mechanical) or virtual (software-based), and are designed to interact with the physical world through sensors and actuators.

ROS (Robot Operating System)

ROS (Robot Operating System) is an open-source middleware framework for robot software development. Despite its name, ROS is not a traditional operating system — it provides tools, libraries, and conventions that simplify the creation of complex and reusable robot software across a wide variety of robotic platforms.

Sensor Fusion

Sensor fusion is the process of combining data from multiple sensors to produce a more accurate, consistent, and reliable estimate of a system's state than any single sensor could provide alone. In robotics, it is essential for tasks like localization, navigation, and perception, where individual sensors have complementary strengths and weaknesses.

SLAM (Simultaneous Localization and Mapping)

SLAM (Simultaneous Localization and Mapping) is the computational problem of constructing or updating a map of an unknown environment while simultaneously tracking a robot's location within it. It is a foundational capability for autonomous mobile robots operating without GPS or pre-built maps.

Z-score

A Z-score (also called standard score) measures how many standard deviations a data point is from the mean in a normal distribution. A positive Z-score indicates the value is above the mean, while a negative Z-score shows it is below. It is widely used in statistics to compare data from different distributions and to calculate probabilities (p-values).