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Technology Innovation Institute’s Secure Systems Research Center in Abu Dhabi Announces Integration of Secure PX4 Stack into RISC-V Based Drone

TII ·

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.

Drift-Corrected Monocular VIO and Perception-Aware Planning for Autonomous Drone Racing

arXiv ·

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.

Visually Guided Balloon Popping with an Autonomous MAV at MBZIRC 2020

arXiv ·

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.

Robust Tightly-Coupled Filter-Based Monocular Visual-Inertial State Estimation and Graph-Based Evaluation for Autonomous Drone Racing

arXiv ·

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.

TII’s Secure Systems Research Center Joins Linux Foundation’s Dronecode

TII ·

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.

The ETH-MAV Team in the MBZ International Robotics Challenge

arXiv ·

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.