VentureOne, the commercialization arm of Abu Dhabi's Advanced Technology Research Council (ATRC), has launched SteerAI, an AI-powered autonomous mobility system that can be integrated into existing industrial vehicles. Developed by experts at the Technology Innovation Institute (TII), SteerAI uses a hardware kit, software stack, and fleet management system. The system targets the logistics and defense sectors, enabling autonomous ground vehicles to perform complex missions with precision and efficiency. Why it matters: This launch underscores the UAE's ambition to become a leader in autonomous vehicle technology, transforming industries and enhancing operational capabilities in critical sectors.
TII's Secure Systems Research Center (SSRC) is partnering with Khalifa University, University of Modena and Reggio Emilia, University of Bologna, University of Waterloo, and McMaster University to develop a RISC-V-based secure flight computer system. The project aims to create an open RISC-V-based System on a Chip (SoC) architecture and software stack for secure application processors in drone flight computers. The collaboration seeks to improve performance, efficiency, reliability, and security relative to current commercial flight computer systems. Why it matters: This international collaboration strengthens the UAE's position in advanced hardware and software co-design for critical applications like drone technology, while also fostering local expertise through partnerships with UAE universities.
A new research paper systematically benchmarked two learning-based and two empirical feedforward steering controllers for autonomous racing, introducing a new Empirical Hysteresis Dynamics (EHD) formulation. The study utilized a high-fidelity simulation framework based on the real-world Abu Dhabi Autonomous Racing League competition. While learning-based controllers showed lower prediction errors in open-loop evaluation, the proposed EHD approach achieved the best overall closed-loop robustness and lap times. Why it matters: This research highlights the critical importance of evaluating control strategies within a complete software stack for autonomous racing, directly informing the development for competitions like the AADRL.
Researchers from the BME Formula Racing Team present the autonomous software stack of the FRED-003C, which enabled full-scale autonomous racing. The software stack was developed in the context of Formula Student Driverless competitions. The paper details the software pipeline, hardware-software architecture, and methods for perception, localization, mapping, planning, and control. Why it matters: The team's experience contributed to their participation in the Abu Dhabi Autonomous Racing League, and sharing the system provides a valuable starting point for other students in the region.
Team TII EuroRacing (TII-ER) developed a full autonomous software stack for oval racing, enabling speeds above 75 m/s (270 km/h). The software includes modules for perception, planning, control, vehicle dynamics modeling, simulation, telemetry, and safety. The team achieved second and third place in the first two Indy Autonomous Challenge events using this stack.
Team NimbRo presented four UAVs tailored for the MBZIRC 2020 challenges, including target chasing, wall building, and fire fighting. The UAVs utilized onboard object detection, aerial manipulation, LiDAR, and thermal cameras to perform their tasks autonomously. The team's software stack, which is mostly open-source, includes tools for system configuration, monitoring, and agile trajectory generation. Why it matters: The work demonstrates advanced robotics capabilities developed in the context of a major regional competition, advancing machine vision and trajectory generation, and showcasing potential applications in various sectors.