ADAM on the move

Artificial Intelligence and Material Handling

Natural Feature Localisation

Evolving from research and development in the field of robotics and artificial intelligence, the ADAM approach uses a simultaneous localisation and mapping (SLAM) technique. This enables a robot to be placed at an unknown location in an unknown environment, and provides the algorithms for the robot to incrementally build a map of this environment while simultaneously using the map to compute its location.

ADAM is given the freedom to consider any open pathway within its environment as a viable route to use when traveling from origin to destination (referred to as open path navigation). Any location within the map boundaries becomes a potential destination for ADAM - without the need for wires, magnetic tape, RFID or reflective targets. This enables tremendous flexibility, allowing ADAM to adapt to changes in the underlying process or application.

Open Path Navigation

In comparison to traditional AGV navigational techniques that typically restrict the vehicles to a fixed path, ADAM has the advantage of open path navigation. This ensures that any pathway to a desired destination is a viable option.

There are no predetermined routings from point A to B. An optimised path to destination is calculated onboard the ADAM itself, but remains dynamic during transport should the vehicle encounter any unexpected obstacles. Although the shortest path to the destination is first calculated, ADAM can recalculate and change the route dynamically if and when required.

Autonomous Traffic Management

In terms of fleet command and control, traffic management and vehicle co-ordination has been greatly simplified. Unlike conventional AGVs that rely on a central control system for direction, traffic coordination in the ADAM system has been transferred down to the vehicle level. 

Each ADAM has the ‘intelligence' to independently resolve any conflicts that might arise while maneuvering through their working environment. ADAM vehicles communicate peer to peer to independently resolve traffic and congestion conflicts as they arise. For example, if one AMR is parked in an aisle waiting to be unloaded, all other vehicles are made aware of the conflict by the parked vehicle and are free to choose an alternative route so that they are able to complete their mission without delay.