Researchers from the US Army have developed a spatial approximation technique to help improve the operations of robots on the battlefield.

Named α-shape, the technique enables multi-robot goal conflict resolution while keeping robots resilient to intermittent communication losses.

The technique was developed collaboratively by researchers from the Army’s Combat Capabilities Development Command (DEVCOM), Army Research Laboratory (ARL) and the University of Nebraska, Omaha Computer Science Department.

US Army researcher Dr Bradley Woosley said: “Robots working in teams need a method to ensure that they do not duplicate effort. When all robots can communicate, there are many techniques that can be used.

“But in environments where robots cannot communicate widely due to needing to stay covert, clutter leading to radios not working for long-distance communications, or to preserve battery or bandwidth for more important messages, the robots will need a method to coordinate with as few communications as possible.”

The technique involves arranging all the regions that robots have explored during missions and combining it with an intelligent search algorithm.

This information is then shared between robots over their communication tree, which allows them to quickly check conflicts of a robot’s selected location.

Experimental results have been reported by the research team on simulated robots and physical Clearpath Jackal robots in different environments.

Woosley added: “To our knowledge, this work is one of the first attempts to integrate geometry-based prediction of potential conflict regions to improve multi-robot information collection under communication constraints, while gracefully handling intermittent connectivity loss between robots.”

Last month, the Army conducted the first production Acceptance Test Procedure (ATP) flights of a Gray Eagle Extended Range (GE-ER) unmanned aircraft system (UAS), in collaboration with General Atomics Aeronautical Systems (GA-ASI).