SHIELD

Interference-Resilient Harmonic ISM Radar for Real-Time Logistics and Distribution

SHIELD

Typical intralogistics operations are characterized by dynamic environments and complex material flows. Logistics processes change continuously, influenced by factors such as warehouse layout, rack locations and dimensions, and the movement of logistics units. With rapid progress in digitalization, it has become easier for companies to deploy autonomous systems. The efficiency of modern material flow systems depends not only on well-structured storage layouts, but also on the speed of mobile robots used for sorting, picking, and transportation. At the same time, employees require reliable information to determine the position of goods at all times.

In logistics environments, robots operate alongside other robots, human workers, and additional logistics assets. In space-constrained warehouses, such shared operation requires substantial coordination. Non-uniform rack contents and occlusions (blind spots) can further increase picking times and storage costs. To ensure high productivity and efficiency, a highly accurate localization system with continuous monitoring of logistics units, implemented as part of a cyber-physical system (CPS), is essential.

The performance of localization technologies in warehouses depends strongly on environmental conditions. In the past, automated guided vehicles (AGVs) used magnetic or optical guidance lines. Today, laser-based SLAM, camera-based SLAM, and RF-based techniques enable greater flexibility and navigation freedom. Laser-based SLAM typically relies on costly LiDAR sensors to build detailed maps while tracking the vehicle’s position within them. In dense and dynamic warehouse environments, challenges arise, for example due to highly variable reflective properties of surrounding objects. Camera-based or visual SLAM (VSLAM) uses images from one or more cameras and applies feature detection and matching algorithms. In warehouse logistics, VSLAM can support both AGV navigation and the identification of specific items; however, its performance is sensitive to lighting variations and other environmental influences.

RF-based localization is used in industrial environments with ultra-wideband (UWB) signals in the 3.6–10.6 GHz band, as well as Bluetooth or Wi-Fi signals. In addition to time-of-flight measurements, approaches may use received signal strength, direction of arrival, and—depending on the technology—time-difference methods, closed-form solutions, or trained fingerprinting. The quality of these methods depends on measurement accuracy. While sub-meter accuracy has been achieved, it is often still insufficient. Significantly higher accuracy requires signal bandwidths that are not currently available under regulatory constraints in lower frequency bands.

Harmonic ISM radar at 61 and 122 GHz enables precise and interference-resilient measurement of wideband echo signals. However, for the described localization use case, the captured data cannot be used directly without further processing. Therefore, it is essential to define and meet the software and hardware requirements, interfaces, and input/output parameters. A particular challenge for the novel 3D positioning approach using distributed and independent radar systems lies in physical implementation and signal processing. Further challenges include integration into industrial environments and robust operation under complex conditions such as multipath propagation or multi-transmitter scenarios. Standard interfaces such as WebSocket and REST, as well as MQTT, support connectivity to external systems.

As part of the project, the FLW Innolab provides a reference test field and a demonstrator for various test scenarios. FLW focuses on evaluating localization and tracking applications for fast-moving AGVs, as well as for stationary logistics assets such as racks and small load carriers (KLT tracking). In addition, FLW contributes logistics expertise to transfer the fundamental developments into industry-ready applications and products. FLW contributes in particular to work packages AP 1, AP 4, AP 5, and AP 6.