MBZUAI researchers are developing LAIKA, an autonomous quadruped robot for hazardous industrial environments, integrating vision-language AI models with 360-degree imaging. LAIKA can operate in operator-assist mode via natural language or autonomously to inspect, detect anomalies like leaks, and generate structured reports. The robot is designed for versatile tasks in industrial inspection, emergency response, and facility monitoring, with future versions integrating multi-robot collaboration. Why it matters: This technology demonstrates AI's potential to enhance industrial safety, reduce risks to human workers, and improve response times in critical situations within the region's vital energy and manufacturing sectors.
Saudi startup Firnas Aero, founded in 2018, offers drone-based inspection services targeting aviation, security, industrial, and delivery sectors. The company develops its own drones and AI-equipped software for faster and more accurate inspections than manual methods. Their solution involves drones capturing high-resolution images analyzed by AI to pinpoint issues, enhancing speed and accuracy. Why it matters: This showcases Saudi Arabia's growing entrepreneurial interest in drone technology and AI-powered solutions for industrial applications, potentially improving efficiency and safety across sectors.
MBZUAI's new robotics department, launched in August 2023, aims to develop AI-driven robotic solutions for key UAE sectors. Professor Dezhen Song, the inaugural Professor of Robotics, highlights the department's focus on the "brain side" of robotics, enhancing perception, navigation, and control. Specific applications include automated infrastructure inspection for the energy sector and AI-driven precision agriculture techniques to improve crop yields and resource efficiency. Why it matters: MBZUAI's robotics research will contribute to the UAE's strategic goals in energy, food security, and sustainable development.
MBZUAI researchers tackled the challenge of AI-powered waste detection in messy, real-world recycling facilities. They fine-tuned modern object detection models on real industrial waste imagery and combined this with a semi-supervised learning pipeline. Fine-tuning more than doubled performance and their semi-supervised pipeline outperformed fully supervised baselines. Why it matters: This research offers a practical path for open research that can rival proprietary systems while reducing the need for costly manual labeling in waste management, a problem of global importance.
In 2012, Saudi Aramco formed an Intelligent Systems team composed primarily of KAUST graduates to prototype robots for oil and gas operations. The team developed SAIR (Saudi Aramco Inspection Robot) in 18 months, a robot capable of visual and ultrasonic inspection of steel assets and gas sensing. SAIR is wirelessly operated, compact, and detects corrosion in hard-to-reach places. Why it matters: This highlights the critical role of KAUST in supplying talent for advanced technology development in Saudi Arabia, particularly in robotics for the energy sector.