London-based autonomous spatial intelligence specialist SLAMcore is partnering German manufacturing and logistics software developer SYNAOS, and the two companies have announced SYNA.OS VIEW, a low-cost, real time, spatial intelligence system for manually guided intralogistics vehicles such as forklifts and warehouse vehicles.

SYNA.OS VIEW is designed to address a growing demand for real-time location and tracking in busy logistics environments. It is a single unit that can be added to existing forklifts, vehicles, and machines to provide accurate real-time locations. The unit uses low-cost stereo cameras and an IMU sensor running on a small, embedded computer and can be simply retrofitted to most vehicles.

SLAMcore’s spatial intelligence software is integrated via an SDK with SYNAOS’ onboard software, allowing real-time location to be constantly communicated with the SYNA.OS LOGISTICS control system through a standardised interface (VDA 5050).

The new system dispenses with the need for expensive UWB positioning or LiDAR systems, often costing up to 15,000 euros. The cost of the SYNA.OS VIEW camera-based system is significantly lower and is designed to offer a wider range of potential applications, and can be easily installed on all kinds of vehicles.

“This collaboration shows the power and flexibility of our vision-based SLAM systems,” said Owen Nicholson, CEO of SLAMcore. “Developed to provide low-cost, high-performance spatial intelligence for robots and autonomous machines, our software delivers accurate, robust Visual SLAM location and mapping to entirely new markets. SYNAOS offers the perfect platform for this type of solution, with expertise in intralogistics and leading customers in manufacturing and logistics markets.”

“SLAMcore is one of the leading providers of localisation, mapping and perception software that converts sensor data into spatial intelligence in real time,” said Dr. Timo Bänziger, Technical Entrepreneur SYNAOS. “We are the first to apply this vision technology to track logistics vehicles and implement real industrial applications applying the benefits of cutting-edge computer vision to manufacturing and logistics.”