TII's Secure Systems Research Center (SSRC) has joined Dronecode, a Linux Foundation non-profit, to enhance UAV security. SSRC will contribute to Dronecode's Security SIG, focusing on cryptography, memory protection, and code analysis for the Pixhawk autopilot hardware and PX4 software. SSRC aims to develop and share security and resilience capabilities for the open UAV platform. Why it matters: This partnership enhances the security of drone systems, addressing potential privacy, cybersecurity, and safety threats in line with the UAE's focus on secure autonomous systems.
TII's Secure Systems Research Center in Abu Dhabi has integrated a secure PX4 stack into a RISC-V based drone, marking a milestone in making RISC-V UAV systems a reality. The center ported DroneCode's PX4 open source software to RISC-V using a commercially available RISC-V development platform. SSRC aims to improve the security and resilience of the PX4 flight control software and NuttX real-time OS, contributing modifications back to the open-source community. Why it matters: This achievement enhances TII's position in drone and autonomous systems research, contributing to safer and more efficient smart city applications in the region.
This paper presents a fully autonomous micro aerial vehicle (MAV) developed to pop balloons using onboard sensing and computing. The system was evaluated at the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020. The MAV successfully popped all five balloons in under two minutes in each of the three competition runs. Why it matters: This demonstrates the potential of autonomous robotics and computer vision for real-world applications in challenging environments.
The paper details the hardware and software systems of ETH Zurich's Micro Aerial Vehicles (MAVs) used in the 2017 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The team integrated computer vision, sensor fusion, and control to develop autonomous outdoor platforms. They achieved second place in Challenge 3 and the Grand Challenge, demonstrating autonomous landing in under a minute and a 90%+ visual servoing success rate for object pickups. Why it matters: The work highlights the advanced state of robotics research and development showcased at the MBZIRC, contributing to the growth of autonomous systems in the region.
This paper details the autonomous drone racing system developed for the Abu Dhabi Autonomous Racing League (A2RL) x Drone Champions League competition. The system uses drift-corrected monocular Visual-Inertial Odometry (VIO) fused with YOLO-based gate detection for global position measurements, managed via Kalman filter. A perception-aware planner generates trajectories balancing speed and gate visibility. Why it matters: The system's podium finishes validate the effectiveness of monocular vision-based autonomous drone flight and showcases advancements in AI-powered robotics within the UAE.
This paper introduces ADR-VINS, a monocular visual-inertial state estimation framework based on an Error-State Kalman Filter (ESKF) designed for autonomous drone racing, integrating direct pixel reprojection errors from gate corners as innovation terms. It also introduces ADR-FGO, an offline Factor-Graph Optimization framework for generating high-fidelity reference trajectories for post-flight evaluation in GNSS-denied environments. Validated on the TII-RATM dataset, ADR-VINS achieved an average RMS translation error of 0.134 m and was successfully deployed in the A2RL Drone Championship Season 2. Why it matters: The framework provides a robust and efficient solution for drone state estimation in challenging racing environments, and enables performance evaluation without relying on external localization systems.
This paper details an autonomous cooperative wall-building system using UAVs developed for Challenge 2 of the MBZIRC 2020 competition. The system employs scanning, RGB-D detection, precise grasping, and multi-UAV coordination to place bricks on a wall. The CTU-UPenn-NYU approach achieved the highest score in the competition by correctly placing the most bricks. Why it matters: This demonstrates advanced capabilities in robotics and autonomous systems relevant for construction and infrastructure development in challenging environments.