36 Dossier | LOXO Alpha & Digital Driver points within the point cloud moved from one moment to the next, and real-time monitoring to prevent error accumulation. “SLAM error minimisation also depends on the quality of your sensors, how well you can fuse the sensor data in a time-synchronised way, whether you’ve integrated powerful and redundant automotive-grade edge computers, and how much you’ve optimised your software, such that it monitors, reacts and even fails over to redundant modules in real time, and so that it doesn’t consume too much power for other onboard functions to continue effectively,” Amini notes. “Downstream from the sensor-fusion engine, we have a combinator engine that combines our RTK- or D-GNSS data with our Lidar SLAM to further detail the vehicle’s localisation information. We had tried visual SLAM in the past, based on camera data, and it does work, but Lidars are inherently the more powerful sensor, especially with the model we use, so Lidar was the better choice for functional safety.” While the Lidar SLAM and RTKGNSS provide different and redundant sources of localisation information, the combinator provides a very precise location fix while also tracking for potential errors in either stream if mismatches occur, and it hence carries intelligence for deciding if the vehicle should switch between one channel or the other. Switzerland’s plethora of tunnels provide the most obvious reason for why LOXO programmed the combinator module to know when to switch from one localisation stream to the next: in any GNSS outage, the Alpha will rely on Lidar SLAM. However, the high precision and fast update rate of the RTK-GNSS means it still plays an important role in LOXO’s localisation, particularly as its accumulated errors over time will naturally be the lowest of any onboard sensor (especially as Alpha’s low speeds and frequent stops between deliveries minimise the chance of GNSS error). To refine its AI models – SLAM, transformer and CNN-based – LOXO used multiple simulation methods, feeling that no single simulation software could be free of weaknesses and so using only one would mean limitations in how far it could validate the models. However, most validations of the Lidar SLAM and Lidar-derived elements of the deep-learning-based autonomy algorithms took place on permitted roads (including on an automotive proving ground near LOXO’s headquarters and on the roads around the innovation park where its HQ sits) due to the considerable limitations of point-cloud simulation technology at present. Two computers plus one Besides three redundant streams of navigation software and four redundant motors at the output end, LOXO’s vehicle architecture centres around what is effectively dual redundant computer architecture. “The first of the two computers can be thought of as our high-performance computer, and the second is there to execute the functions under LOXO Guard, which pertain to functional safety requirements, analysing incoming streams of data from the first computer to check and approve LOXO Fuser’s decisions against information output by the other two software AI models,” Amini says. While the exact models of computer installed will vary based on the project budget, as well as exact customer operational and fleet requirements, the former of the two computers is typically based on an Nvidia GPU-powered solution, such as the Jetson Orin, to achieve the high computing power and performance needed for LOXO’s AI models. The company also notes that some hardware suppliers now provide the latest Nvidia autonomy computers within automotive-grade hardware modules, built to be compliant with (and hence certifiable to) ISO 26262, and therefore present great promise for future integrations and collaborations. “Meanwhile, we use a range of certified, automotive-grade computers for running safety-critical functions, which are available commercially on the market,” Amini says. “Finally, we have a third computer, which essentially monitors the health of the two primary operating computers to ascertain that they’re functioning and interacting correctly. “If one or both are not doing so, that third computer can take over the self-driving functions in a degraded mode. That mode consists mainly of just using the Lidars and a very slow driving speed to pull over and get off the road safely.” April/May 2025 | Uncrewed Systems Technology In the event of GNSS outages, the Alpha runs on a Lidar SLAM system, which LOXO has precisely engineered for quality data fusion, tight reaction times, power efficiency and many other factors
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