Simultaneous Localisation and Mapping (SLAM), a technology which allows a device to map its environment while positioning itself in it, is a crucial driver for the future of robotics.
SLAM software enables the transition from Automated Guided Vehicles (AGVs) to Autonomous Mobile Robots (AMRs) in the industrial space.
As such, the install base of SLAM-enabled Autonomous Mobile Robots will exceed 15 million by 2030, according to global tech market advisory firm ABI Research.
For many years, business owners in the industrial sector have been using AGVs in factories and warehouses to streamline their processes, increase production and reduce inventory counting time, among other tasks.
Today, AMRs comprise a new generation of industrial robots that can optimise their paths and processes on the factory floor, react to unexpected situations, and navigate around obstacles.
But to coordinate factory activities and avoid collisions between AMRs, AGVs, and people, a real-time location system (RTLS) which can pinpoint the location of every robot must be in place.
Not many manufacturing sites currently have such an RTLS, creating a need for AMRs that can dynamically map their immediate environment using SLAM software.
However, those factories which have already deployed RTLS can use it in conjunction with SLAM to provide valuable data to a digital platform that can be used to optimise processes and drive efficiencies, thereby driving much faster ROI.
Deploying robots on the factory floor is already allowing organisations to save substantial amounts of money in labour and insurance, as well as increase productivity.
Unlocking future gains is likely to come from more intelligent and easily reprogrammable robots such as AMRs, which are predicted by ABI Research to comprise 80% of all commercial robot shipments by 2027.
All AMRs must possess mapping and localisation capabilities to react to the fast-changing environment inside factories to avoid collisions with other machines and humans.
Therefore, most industrial robots are expected to have SLAM capabilities in the next decade, powered by sophisticated algorithms to work smoothly and accurately.
Data generated by these robots’ SLAM capabilities can also be integrated into a centralised digital factory platform to be analysed for KPIs.
“The 2020s are going to kick off with drastic changes in industrial environments,” notes Andrew Zignani, principal analyst for Location Technologies at ABI Research.
“AI, IoT, RTLS, and connectivity technologies such as 5G will interact and improve each other in complex ways, and not all levels of the robotics value chain are ready for it. There are great opportunities in software development yet to be explored, SLAM being a big part of it.”