Glossary

An autonomous forklift, also known as a driverless forklift or automated guided forklift (AGF), is a self-operating industrial vehicle designed to perform traditional forklift tasks.

The term is used to describe a robot or a robotic vehicle requiring no direct human operator or a guidance system to operate.

An automated storage system, off-limits to humans, where goods are placed and retrieved from storage in a centrally-run computer-operated system.

Autonomous Mobile Robots (AMRs) are self-driving robotic vehicles that can plot their own path to a given destination, navigate around obstacles, and perform tasks – all without the direct control of humans.

A cobot, or as it is also known, a collaborative robot, is a type of robot or robotic vehicle designed to work safely with and around humans.

The capability of an autonomous mobile robot or a robotic vehicle to use camera inputs to estimate depth with no other sensor data.

A full 3D map of the environment, with all visible surfaces included in the map.

A material-handling automation use case that involves autonomous mobile robots (AMRs) or automated guided vehicles (AGVs) following a person around the facility.

Fleet Management refers to software solutions for setting up and controlling a fleet of autonomous mobile robots or robotic vehicles.

Goods to Person is an order fulfillment method using automation to bring the stock to pickers. It can involve autonomous mobile robots (AMRs), automated guided vehicles (AGVs), or automated storage and retrieval systems (AS/RS).

Instance segmentation is the capability of an autonomous robot or robotic vehicle to detect separate instances of the same type of object.

LiDAR stands for Light Detection And Ranging. LiDAR is a sensor technology that is often called a laser, but the popular radar inspired the acronym.

An umbrella term covering technologies, equipment and processes minimizing human input in material handling.

Some autonomous mobile robots have the capability of building 3D maps of the environment in which they operate.

The capability of a moving autonomous vehicle to predict the motion of other objects based on their apparent motion in its field of view.

Object tracking is the capability of an autonomous robot or a robotic vehicle to track separate objects in its field of vision.

Pose estimation is the capability of a robot or a robotic vehicle to estimate the exact pose of an object – for example, a pallet – in space.

A robot forklift is an autonomous or semi-autonomous robot designed to perform traditional forklift tasks such as lifting, moving, and placing palletized goods without human intervention.

Robot vision is the capability of a robot to perceive and understand its environment by processing camera inputs usually involving some of the machine learning approaches.

Robot localization refers to the process of a robot determining its location in an environment usually represented by a map.

An order fulfillment method involving complex coordination of autonomous mobile robots (AMRs).

A pair of cameras enabling advanced visual perception, including depth estimation, just like a pair of eyes.

A sparse 3D map is a simplified three-dimensional representation created by autonomous mobile robots that consists of discrete data points highlighting distinctive features in the environment.

Simultaneous localization and mapping (also known as SLAM) is an algorithm that allows autonomous mobile robots or vehicles to construct a map of their surroundings and determine their location in that environment.

The capability of an autonomous mobile robot to understand what surrounds them – to detect separate objects and recognize what those objects are.

Sensor fusion is the process of combining data from various sensors – for example, 2D LiDAR and stereo cameras.

vSLAM is a type of SLAM algorithm based on robot vision. vSLAM uses inputs from monocular, stereo, or RGB-D cameras.

vAMRs are autonomous mobile robots that utilize advanced visual perception technologies to navigate and operate in their environment.