ZaiNar has announced the commercial availability of a 5G positioning system that operates independently of device manufacturers and satellite navigation. The company states that its technology delivers sub-10 centimeter accuracy at distances of up to 1.5 kilometers by using standard connectivity signals already transmitted by devices connected to a 5G network.
The system differs from conventional positioning approaches that rely on GPS, ultra-wideband, WiFi triangulation or dedicated positioning reference signals. Instead, it uses Sounding Reference Signals, which devices must transmit to maintain their 5G connection. Because these signals are sent between 100 and 500 times per second, the network can track fast-moving objects in real time. According to the company, this enables positioning for robots, drones, vehicles and other connected machines without additional hardware, device-level software or increased battery consumption.
By shifting positioning from the device to the network layer, the approach removes dependence on operating system permissions or manufacturer cooperation. Location becomes a function of the 5G infrastructure itself. ZaiNar reports that the technology has demonstrated sub-10cm accuracy on CBRS Band 48 networks using 20 MHz of spectrum and can operate on as little as 10 MHz, making it suitable for private 5G and low-power IoT environments.
For robotics, the development is particularly relevant in environments where GPS is unreliable or unavailable, such as factories, warehouses and construction sites. Today, many robots rely on onboard camera systems and simultaneous localization and mapping (SLAM) algorithms to determine their position. These methods require significant compute resources and can experience drift over time, especially in large or changing environments. A network-based positioning layer could allow robots to offload part of this localization workload to the 5G network, reducing onboard processing demands while maintaining continuous spatial awareness.
The system also enables the network to provide real-time location data for all connected devices within coverage. In multi-robot deployments, this could support coordinated navigation, fleet management and collision avoidance without relying solely on line-of-sight sensing. Because radio signals propagate consistently and can be synchronized at sub-nanosecond precision, centimeter-level positioning can be derived from timing differences in standard connectivity transmissions.
ZaiNar positions the technology as foundational infrastructure for what it describes as Physical AI, referring to AI systems operating in the physical world rather than purely digital environments. In this context, continuous and accurate spatial data is considered essential for both coordination and training of autonomous systems.
The company states that its positioning system is already deployed commercially across healthcare, construction, logistics and smart city applications on multiple continents. It reports securing more than $450 million in contracts and memoranda of understanding, with additional carrier and enterprise partnerships expected to be announced. For the robotics sector, the announcement underscores a broader trend in which telecom networks are evolving from connectivity platforms into sensing infrastructure capable of supporting autonomous machines that can operate indoors and outdoors without relying on GPS.
