Robot Industry Glossary

The application of IoT in industrial settings for monitoring and control.

The calculation of joint angles required to place a robot’s end-effector at a desired position and orientation, often computationally challenging.

Training robots by observing expert demonstrations (human or synthetic), bypassing manual reward function design.

A motion-based control strategy where a robot behaves like a mechanical impedance (mass-spring-damper) at its end-effector for compliant interaction.

A device combining accelerometers and gyroscopes (sometimes magnetometers) to measure orientation, velocity, and gravitational forces.

Integration of robots, PLCs, and conveyors to perform repetitive manufacturing tasks with high precision and throughput.

A programmable, automated machine used in manufacturing for tasks like welding, painting, assembly, and material handling, typically in a caged environment.

The fourth industrial revolution characterized by smart factories, IoT, AI, and interconnected autonomous robots and systems.

The resistance of a robot’s body or link to changes in its state of motion; a key parameter in dynamic modeling and control.

A sensor that measures acceleration and angular velocity to determine orientation and movement.

A self-contained navigation method using IMU data to estimate a robot’s position and orientation without external references.

A robot designed to examine infrastructure, pipelines, buildings, or industrial equipment for defects, corrosion, or wear.

A software application providing comprehensive tools for writing, testing, and debugging robot control programs.

A complete workcell with robot, machine(s), safety systems, and controls.

The process of combining robot hardware, software, sensors, and tooling into a complete working system for a specific application.

A robot equipped with AI capabilities enabling it to perceive, learn, reason, and adapt to complex and changing environments.

Algorithms that predict human goals from gestures, gaze, voice, or physiological signals to enable proactive robot responses.

The calculation of required joint torques/forces to produce a desired robot motion, essential for model-based control.

The computation of joint angles required to achieve a desired end-effector position and orientation.

The network of interconnected devices and sensors that enables robots to share data and coordinate with other systems over the internet.

A ruggedized computer used to run robot control software in harsh industrial environments with real-time requirements.

NVIDIA’s robotics simulation platform for designing, testing, and training robots using synthetic data and GPU-accelerated physics.

International standards defining safety requirements for industrial robots and collaborative robot applications.

An algorithm that aligns two point clouds or 3D scans by iteratively minimizing the distance between corresponding points, used in SLAM and object recognition.