Robotics and autonomous systems research from the Gulf region, including work from MBZUAI, Khalifa University, and TII on robot learning and embodied AI.
Technology Innovation Institute (TII) has launched a state-of-the-art research facility within its Directed Energy Research Center (DERC) in Abu Dhabi's Tawazun Industrial Park. The facility includes seven workshops and five specialized laboratories focusing on areas like High-Power ElectroMagnetics (HPEM), acoustics, and laser development. It can accommodate 150 researchers and provides research and testing services to local industries, including Radio Frequency testing and acoustic experiments. Why it matters: This new facility enhances the UAE's research infrastructure and supports the development of advanced technologies for regional industries in the safety and security sector.
ARRC researchers in collaboration with the University of Bologna and ETH Zürich have developed a CNN-based AI deck to enable autonomous navigation of a 27g nano-drone in unknown environments. The CNN allows the drone to recognize and avoid obstacles using only an onboard camera, running 10x faster and using 10x less memory than previous versions. The demo also featured a swarm of nano-drones flying in formation using ultra-wideband communication. Why it matters: This advancement could significantly enhance the capabilities of nano-drones for applications such as disaster response, where quick and efficient intervention is crucial.
Technology Innovation Institute's (TII) Directed Energy Research Center (DERC) in Abu Dhabi has launched the GCC region's first Laser-Matter Interaction (LMI) Laboratory. The LMI Lab, part of DERC's Laser, Photonics, and Optoelectronics Division, will investigate laser interactions with matter. This lab will enable local research and development in laser materials processing, plasma physics, and nanotechnology, reducing reliance on foreign outsourcing. Why it matters: This regional first enhances the UAE's position in advanced technology research and expands the application of lasers across diverse industries in the GCC.
TII's Secure Systems Research Center (SSRC) in Abu Dhabi has launched a motion capture (MOCAP) facility for testing drones in augmented reality, the first such facility outside the US. SSRC's MOCAP facility will simulate environments like Abu Dhabi city to enable high-precision ground truth for experiments. The facility will allow the modelling and operation of a cloud-based secure autonomous system of drones. Why it matters: This positions the UAE as a leader in drone security research, enabling advanced testing and development of secure drone systems for various critical applications.
A team led by the Technology Innovation Institute (TII) in Abu Dhabi has developed NATHR-G1, a ground penetrating radar for detecting landmines and unexploded ordnance. The project, involving researchers from Colombia, Germany, Sweden, and Switzerland, builds on earlier work using radar to detect buried objects. NATHR-G1 incorporates machine learning for advanced signal processing and object identification. Why it matters: This humanitarian application of AI and robotics based in the UAE could significantly reduce casualties from landmines and other explosive remnants of war.
The Technology Innovation Institute (TII) in Abu Dhabi has begun constructing the UAE's first quantum computer. The project started with the arrival of a 300-part cryostat from Finland, designed to cool the computer's brain to extremely low temperatures. The quantum computer will leverage quantum mechanics principles to enhance computational efficiency. Why it matters: This initiative positions the UAE as a regional leader in quantum computing, with potential advancements in fields like medicine, battery technology, and AI.
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.
Technology Innovation Institute (TII) has launched Electromagnetic Compatibility (EMC) laboratories in Abu Dhabi, the first such facility in the Arab world. The facility at TII's Directed Energy Research Center (DERC) includes three labs: an EMC semi-anechoic chamber, a pulsed power laboratory, and a low-noise emanation laboratory. These labs will enable evaluation of technologies against electromagnetic interference and support in-country R&D and local industry in line with UAE's 'Operation 300bn'. Why it matters: This advanced infrastructure signals the UAE's commitment to fostering innovation in electronics and related sectors, reducing reliance on foreign testing and certification.
TII's Secure Systems Research Center (SSRC) has announced partnerships with Khalifa University, Georgia Institute of Technology, Tampere University, and SUPSI across multiple projects. These collaborations aim to advance secure systems research, with Khalifa University focusing on machine learning for exfiltration detection and secure drone communication, Georgia Tech working on attack-resilient software for cyber-physical systems, Tampere University focusing on critical infrastructure security, and SUPSI exploring AI-based secure autonomous navigation on Nano-UAVs. Why it matters: These partnerships highlight the UAE's commitment to advancing research and development in secure systems and autonomous technologies, fostering innovation and expertise in critical areas like cybersecurity and UAV technology.
The Technology Innovation Institute (TII) in Abu Dhabi announced its Quantum Research Center (QRC) will build the UAE’s first quantum computer in collaboration with Qilimanjaro Quantum Tech. The computer will use superconducting qubits, the same technology used by Google and IBM. The first quantum chips are expected by the end of summer. Why it matters: This project positions the UAE as a leader in quantum computing research and development in the Middle East, potentially enabling breakthroughs in medicine, materials science, and AI.
TII's Secure Systems Research Center (SSRC) has partnered with Purdue University on a three-year cybersecurity project focused on ensuring the safe and efficient use of Unmanned Aerial Vehicles (UAVs) in urban environments. The collaboration will study security and resilience in cyber-physical and autonomous systems, addressing vulnerabilities in communication, navigation, and command and control. The project includes four phases: modeling and analysis of UAS security, developing algorithms for high-assurance autonomy, constructing an experimental environment, and testing mitigation strategies. Why it matters: The partnership enhances the UAE's capabilities in securing critical digital systems and fosters the growth of commercial autonomous drones and robots, opening new opportunities for enterprises.
TII and Virgin Hyperloop have announced a research and development partnership to advance hyperloop technology in the UAE. The collaboration will focus on pulsed power, magnetic levitation, and material sciences at TII's premises. The partnership involves cooperation between TII’s Directed Energy Research Center (DERC), Autonomous Robotics Research Center (ARRC) and Advanced Materials Research Center (AMRC). Why it matters: This partnership strengthens the UAE's position as a global research hub for advanced transportation and sustainable energy solutions, potentially driving economic growth and innovation in the region.
The Advanced Technology Research Council (ATRC) has launched ASPIRE, a technology program management pillar to drive the creation of transformative technologies. ASPIRE will define problem statements, set milestones, allocate funding, and launch grand challenges to facilitate a path from lab to market. ASPIRE will also run the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) and launch a global competition in partnership with the XPRIZE Foundation. Why it matters: This initiative strengthens Abu Dhabi and the UAE's position as an international hub for advanced technology research and development, fostering innovation and contributing to a knowledge-based economy.
Abu Dhabi has launched the Technology Innovation Institute (TII) as the applied research arm of the Advanced Technology Research Council (ATRC). TII will focus on seven initial research centers including quantum research, autonomous robotics, and cryptography. The institute has already partnered with over 20 universities on 25 long-term projects, aiming to establish Abu Dhabi and the UAE as a global hub for advanced technology research. Why it matters: This initiative signals a major investment in R&D infrastructure and talent recruitment, potentially accelerating technological advancements and diversifying the UAE's economy.
Abu Dhabi’s Advanced Technology Research Council (ATRC) held its first board meeting, led by Sheikh Khaled bin Mohamed bin Zayed Al Nahyan, to establish R&D priorities for the emirate. ATRC will focus on fostering public-private partnerships, creating talent development programs, and aligning investments in scientific inquiry. The council ratified seven priority areas: quantum, autonomous robotics, cryptography, advanced materials, digital security, directed energy, and secure systems. Why it matters: This initiative signals Abu Dhabi's commitment to becoming a hub for advanced technology research and development, with a focus on attracting global talent and fostering innovation in key technological areas.
Technology Innovation Institute (TII) and the World Economic Forum (WEF) have launched the Abu Dhabi Centre for Frontier Technologies. The center will focus on Quantum Computing, Robotics, Propulsion & Space systems, and related AI applications. It will operate within WEF’s Centre for the Fourth Industrial Revolution (C4IR) Global Network. Why it matters: This partnership positions Abu Dhabi as a global hub for advanced technology research and strengthens the UAE's role in shaping the global technology agenda.
The Technology Innovation Institute (TII) and Resource Industries have partnered to integrate autonomous air system technologies into operational defense platforms. The collaboration will embed TII's research, including synthetic aperture radar (SAR) and radio frequency (RF) magnetic mapping, into Resource Industries' aerial platforms. The aim is to enhance intelligence gathering and decision-making in complex environments. Why it matters: This partnership signifies the UAE's commitment to advancing its defense capabilities through indigenous innovation and autonomous systems, aligning with national strategies for technological advancement.
Technology Innovation Institute (TII) and Qualcomm Technologies are collaborating to advance edge-AI and autonomous solutions. The partnership will combine TII's robotics expertise with Qualcomm's edge-computing platforms to develop intelligent systems for complex environments. TII will explore Qualcomm's Dragonwing IQ9 and IQ10 platforms to build robots for sectors like energy, mining, construction, and smart cities. Why it matters: This collaboration strengthens the UAE's position in developing advanced autonomous systems and edge-AI technologies for critical industries, fostering innovation and economic growth.
The Technology Innovation Institute (TII) and NYU Abu Dhabi (NYUAD) have signed a collaboration agreement to deepen strategic collaboration in research, education, and talent development. The partnership includes a Research and Development Sponsorship Agreement and a Framework Fellowship Program Agreement. TII and NYUAD will collaborate on joint research projects across areas like AI, robotics, and quantum science, and TII will sponsor NYUAD students for research in priority technology domains. Why it matters: The partnership aims to bridge fundamental research with real-world applications, accelerate scientific discovery, and develop a pipeline of skilled researchers in Abu Dhabi.
Robo.ai, a robot data company, is leveraging the United Arab Emirates' ambitious $100 billion investment into artificial intelligence to power its business growth. The company focuses on collecting and processing data generated by robots, which is crucial for training and improving AI models in robotics applications. This strategic alignment positions Robo.ai to benefit from the UAE's national drive to become a global leader in AI and advanced technologies. Why it matters: This development demonstrates a tangible example of how the UAE's significant national AI investments are translating into ecosystem growth and specialized industry development within the region.
This study introduces a reinforcement learning (RL) framework using Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) to optimize the cleaning schedules of photovoltaic panels in arid regions. Applied to a case study in Abu Dhabi, the PPO-based framework demonstrated up to 13% cost savings compared to simulation optimization methods by dynamically adjusting cleaning intervals based on environmental conditions. The research highlights the potential of RL in enhancing the efficiency and reducing the operational costs of solar power generation.
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.
The UAE has reportedly asserted its position as a global leader in the fields of autonomous systems and future engineering. This claim of leadership was highlighted by the Emirates News Agency (wam.ae). The announcement underscores the nation's strategic focus on pioneering advanced technological development. Why it matters: This statement reflects the UAE's ambitious national strategy to be at the forefront of emerging technologies and attract related investment and talent.
The paper presents MonoRace, an onboard drone racing approach using a monocular camera and IMU. The system combines neural-network-based gate segmentation with a drone model for robust state estimation, along with offline optimization using gate geometry. MonoRace won the 2025 Abu Dhabi Autonomous Drone Racing Competition (A2RL), outperforming AI teams and human world champions, reaching speeds up to 100 km/h. Why it matters: This demonstrates a significant advancement in autonomous drone racing, achieving champion-level performance with a resource-efficient monocular system, validated in a real-world competition setting in the UAE.
This paper introduces a hybrid deep learning and machine learning pipeline for classifying construction and demolition waste. A dataset of 1,800 images from UAE construction sites was created, and deep features were extracted using a pre-trained Xception network. The combination of Xception features with machine learning classifiers achieved up to 99.5% accuracy, demonstrating state-of-the-art performance for debris identification.
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.
The paper introduces OmniGen, a unified framework for generating aligned multimodal sensor data for autonomous driving using a shared Bird's Eye View (BEV) space. It uses a novel generalizable multimodal reconstruction method (UAE) to jointly decode LiDAR and multi-view camera data through volume rendering. The framework incorporates a Diffusion Transformer (DiT) with a ControlNet branch to enable controllable multimodal sensor generation, demonstrating good performance and multimodal consistency.
Abu Dhabi is spearheading the development of a comprehensive regulatory framework for air taxis within the UAE. This initiative aims to establish a global model for rules governing urban air mobility. The framework focuses on safely integrating advanced aerial technologies into the future transportation ecosystem. Why it matters: This positions the UAE as a forward-thinking leader in shaping the future of advanced aerial transport and setting international precedents for this emerging industry.
This paper introduces a framework that combines machine learning for multi-class attack detection in IoT/IIoT networks with large language models (LLMs) for attack behavior analysis and mitigation suggestion. The framework uses role-play prompt engineering with RAG to guide LLMs like ChatGPT-o3 and DeepSeek-R1, and introduces new evaluation metrics for quantitative assessment. Experiments using Edge-IIoTset and CICIoT2023 datasets showed Random Forest as the best detection model and ChatGPT-o3 outperforming DeepSeek-R1 in attack analysis and mitigation.
KAUST and Aramco have signed an IP license agreement for the Hybrid Unmanned Aerial Vehicle Crawler Technology (HUCT), which combines aerial and terrestrial robotic capabilities. The HUCT will be used for inspection, monitoring, and other industrial applications within Aramco's operations. The agreement supports KAUST's mission to translate research into real-world applications, aligned with Saudi Vision 2030. Why it matters: This partnership demonstrates the growing innovation ecosystem in Saudi Arabia, leveraging academic research for industrial applications in robotics and AI.
Researchers introduce MATRIX, a vision-centric agent tuning framework for robust tool-use reasoning in VLMs. The framework includes M-TRACE, a dataset of 28.5K multimodal tasks with 177K verified trajectories, and Pref-X, a set of 11K automatically generated preference pairs. Experiments show MATRIX consistently outperforms open- and closed-source VLMs across three benchmarks.
Kuwait has successfully conducted the farthest remote robotic surgery, an achievement recognized by Guinness World Records. This pioneering medical procedure showcased advanced capabilities in tele-operation and robotic technology within the healthcare sector. The specific details of the technology used and the medical context were highlighted in the record-setting event. Why it matters: This accomplishment signifies a major leap in medical innovation and remote healthcare capabilities for Kuwait and the broader Middle East region.
Researchers propose MS-NN-steer, a model-structured neural network for autonomous vehicle steering control that integrates nonlinear vehicle dynamics. The controller was validated using real-world data from the Abu Dhabi Autonomous Racing League (A2RL) competition. MS-NN-steer demonstrates improved accuracy, generalization, and robustness compared to general-purpose NNs and the A2RL winning team's controller. Why it matters: This research demonstrates a promising approach to developing transparent and reliable AI for safety-critical autonomous racing applications in the UAE.
Researchers from MBZUAI have introduced VideoMolmo, a large multimodal model for spatio-temporal pointing conditioned on textual descriptions. The model incorporates a temporal module with an attention mechanism and a temporal mask fusion pipeline using SAM2 for improved coherence across video sequences. They also curated a dataset of 72k video-caption pairs and introduced VPoS-Bench, a benchmark for evaluating generalization across real-world scenarios, with code and models publicly available.
MBZUAI introduces Agent-X, a benchmark for evaluating multi-step reasoning in vision-centric agents across real-world, multimodal settings. Agent-X includes 828 tasks with diverse visual contexts and spans six environments, requiring tool use and stepwise decision-making. Experiments show that current LLMs struggle with multi-step vision tasks, achieving less than 50% success, highlighting areas for improvement in LMM reasoning and tool use.
KAUST researchers have developed a hybrid cooling technology combining nanotech plastic and biodegradable mulch that significantly enhances crop yields in arid regions. The technology lowers greenhouse temperatures by 25 degrees Celsius and doubles crop yields in tests with Chinese cabbage. The nanotech plastic coating absorbs infrared light, while the biodegradable mulch reflects sunlight to keep the soil cooler. Why it matters: This innovation promises to improve food security in arid regions like Saudi Arabia while reducing energy consumption and plastic waste associated with traditional greenhouse cooling methods.
MBZUAI researchers introduce LLM-BabyBench, a benchmark suite for evaluating grounded planning and reasoning in LLMs. The suite, built on a textual adaptation of the BabyAI grid world, assesses LLMs on predicting action consequences, generating action sequences, and decomposing instructions. Datasets, evaluation harness, and metrics are publicly available to facilitate reproducible assessment.
Saudi Arabia's Ministry of Transport and Logistic Services (MOTLS) and KAUST, in collaboration with the Ministry of Industry and Mineral Resources, are launching the Future Mobility Sandbox, a 1.56 square kilometer testbed on the KAUST campus. It will enable testing of air, land, and sea transport innovations. The initiative aims to create safer, more efficient, and sustainable mobility solutions. Why it matters: The sandbox will foster innovation in autonomous, sustainable, and connected transport, positioning Saudi Arabia as a hub for advanced mobility technology and attracting global investment.
Researchers at MBZUAI have introduced a novel approach to enhance Large Multimodal Models (LMMs) for autonomous driving by integrating 3D tracking information. This method uses a track encoder to embed spatial and temporal data, enriching visual queries and improving the LMM's understanding of driving scenarios. Experiments on DriveLM-nuScenes and DriveLM-CARLA benchmarks demonstrate significant improvements in perception, planning, and prediction tasks compared to baseline models.
KAUST researchers, in collaboration with KACST, discovered that dissolving nylon in battery electrolytes improves the performance of lithium-metal batteries. The nylon additive resulted in more efficient batteries with longer lifespans and fewer unwanted reactions. The research was published in ACS Energy Letters and Energy Environmental Science. Why it matters: This promises cheaper, safer, and more powerful lithium batteries for applications in electric vehicles and aviation, supporting Saudi Arabia's renewable energy goals.
KAUST is developing a robotic system for automated date palm harvesting, combining robotics and AI. The system uses robotic arms with visual sensors to identify and harvest dates, flowers, and tree structures. Field trials are scheduled for the 2025 harvest season, with full operational capability expected within three years. Why it matters: This innovation could transform Saudi Arabia's date farming industry, increasing yields, reducing labor risks, and positioning the country as a leader in agricultural technology.
KAUST and the National Center for Palm and Dates (NCPD) have entered a SR100 million agreement for research projects in the date palm sector. The agreement aims to improve production efficiency, develop innovative agricultural practices, and mitigate economic risks to palm trees. KAUST will leverage its expertise to create a genetic atlas for Saudi date varieties and adopt sustainable management practices. Why it matters: This investment highlights Saudi Arabia's commitment to its cultural heritage and economic diversification through advancements in a key agricultural sector.
KAUST and Saudi Aramco collaborated to develop a laser-based sensor for detecting trace amounts of gas leaks in petrochemical plants. The sensor uses machine learning to identify specific gases, differentiating it from previous sensors that only detect large leaks. The technology can differentiate between closely related industrial gases like benzene, toluene, ethyl benzene and xylene (BTEX). Why it matters: This innovation enables proactive monitoring and rapid pinpointing of leaks, enhancing safety, environmental protection, and operational efficiency in the petrochemical industry.
Researchers introduce TomFormer, a transformer-based model for accurate and early detection of tomato leaf diseases, with the goal of deployment on the Hello Stretch robot for real-time diagnosis. TomFormer combines a visual transformer and CNN, achieving state-of-the-art results on KUTomaDATA, PlantDoc, and PlantVillage datasets. KUTomaDATA was collected from a greenhouse in Abu Dhabi, UAE.
The study introduces the Qatar University Dual-Machine Bearing Fault Benchmark dataset (QU-DMBF) containing sound and vibration data from two motors across 1080 conditions. It proposes a deep learning approach for sound-based fault detection, addressing limitations of vibration-based methods. Experiments on QU-DMBF show sound-based detection is more robust, independent of sensor location, and cost-effective while matching vibration-based performance. Why it matters: The new dataset and findings could shift the focus toward sound-based methods for more reliable and accessible predictive maintenance in industrial settings.
MBZUAI researchers introduce PG-Video-LLaVA, a large multimodal model with pixel-level grounding capabilities for videos, integrating audio cues for enhanced understanding. The model uses an off-the-shelf tracker and grounding module to localize objects in videos based on user prompts. PG-Video-LLaVA is evaluated on video question-answering and grounding benchmarks, using Vicuna instead of GPT-3.5 for reproducibility.
Researchers at the Technology Innovation Institute (TII) have released a fully-annotated dataset for autonomous drone racing, called "Race Against the Machine." The dataset includes high-resolution visual, inertial, and motion capture data from both autonomous and piloted flights, along with commands, control inputs, and corner-level labeling of drone racing gates. The specifications to recreate their flight platform using commercial off-the-shelf components and the Betaflight controller are also released. Why it matters: This comprehensive resource aims to support the development of new methods and establish quantitative comparisons for approaches in robotics and AI, democratizing drone racing research.
Ceer and KAUST are partnering to research and develop innovations in smart mobility, including connectivity and autonomous driving technologies. The collaboration aims to transform research into economically productive innovations, supporting Saudi-based SMEs and the automotive manufacturing industry. Ceer and KAUST will share facilities and conduct collaborative activities to foster knowledge exchange and create jobs. Why it matters: This partnership signifies a crucial step towards diversifying Saudi Arabia's economy and advancing technological capabilities in the electric vehicle sector within the Kingdom.
This paper introduces a convolutional transformer model for classifying tomato maturity, along with a new UAE-sourced dataset, KUTomaData, for training segmentation and classification models. The model combines CNNs and transformers and was tested against two public datasets. Results showed state-of-the-art performance, outperforming existing methods by significant margins in mAP scores across all three datasets.
Al-Miyah Solutions, a KAUST spin-off, has installed a decentralized wastewater treatment unit in Rabigh, Saudi Arabia. The mobile, modular technology converts wastewater into reusable water for areas lacking centralized sewer access, addressing a need for 40% of Saudi households. The technology, developed at KAUST's Water Desalination and Reuse Center, uses aerobic granular sludge and gravity-driven membrane filtration. Why it matters: This deployment offers a sustainable and cost-effective solution for wastewater treatment and reuse in remote areas of the Kingdom, reducing reliance on costly centralized systems.