Automated: Computer-controlled machines that can perform a set of defined tasks by following specific instructions with minimal or no human intervention.
Autonomous: Machines that have the intelligence to make decisions when faced with new or unexpected situations.
These machines may have the ability to learn as they encounter new situations.
AGV vs SDV
Automated Guided Vehicles (AGVs) and Self-Driving Vehicles (SDVs) are also often confused.
Each system operates with fundamentally different technology, from perception and navigation software to onboard sensors.
Therefore, they have different capabilities and potential applications.
Automated Guided Vehicle (AGV):
An AGV is an unmanned electric vehicle that is controlled by pre-programmed software to move materials around a facility.
AGVs rely on guidance devices such as magnetic tape, beacons, barcodes or predefined laser paths that allow the AGV to travel on fixed paths in a controlled space.
Lasers and sensors detect obstacles in its path and trigger the vehicle to stop automatically.
Self-Driving Vehicle (SDV):
An SDV is a vehicle in which operation occurs without direct driver input or pre-configured scripts to control the steering, acceleration, and braking.
Within an industrial environment, an SDV utilizes laser-based perception and navigation algorithms to dynamically move through facilities, infrastructure-free.
Machine learning capabilities enable the vehicle to become more efficient and accurate as it encounters new situations.
The SDV: An evolution of the AGV
Automated material transport has experienced an evolution due to rapid advancement in sensors and big data capability.
Autonomous next-generation solutions are disrupting conventional AGV technologies with 5 core advantages (described in detail in this white paper).