Robotics and autonomous systems research from the Gulf region, including work from MBZUAI, Khalifa University, and TII on robot learning and embodied AI.
Five Emirati researchers from the Directed Energy Research Center (DERC) concluded a 5-week training course in Switzerland on laser processing and laser-matter interaction at Empa-Swiss Federal Laboratories. The training involved hands-on experience with high-end equipment to conduct independent research. The DERC researchers will contribute to DERC’s projects and help operate its AI-powered laser-matter interaction laboratory. Why it matters: This international training enhances local expertise in advanced laser technology, crucial for developing AI-driven material science capabilities in the UAE.
Prof. George Alexandropoulos from the AI and Digital Science Research Center (AIDRC) at TII presented a keynote at the RIS Technical Alliance (RISTA) forum. The presentation focused on hybrid reconfigurable intelligent surfaces for wireless communication and sensing applications. He discussed the role of RIS technology in enabling smart wireless environments within 5G and 6G networks. Why it matters: This highlights the UAE's contribution to cutting-edge research in next-generation wireless communication technologies and its potential impact on future network architectures.
The Technology Innovation Institute (TII) will host the GlobalEM high-power electromagnetics conference in Abu Dhabi from November 13–17. The conference, organized by TII’s Directed Energy Research Center (DERC), will feature sessions on sources, antennas, IEMI threats, high energy lasers, and critical infrastructure impacts. GlobalEM brings together experts to discuss challenges and opportunities in electromagnetics. Why it matters: The event strengthens the advanced directed energy domain in the UAE and supports Abu Dhabi's goal of becoming a hub for innovation in mitigating electromagnetic risks.
The Technology Innovation Institute's (TII) Advanced Materials Research Center (AMRC) will host an in-person seminar titled ‘Additive Manufacturing the Future’ on May 19 in Abu Dhabi. The seminar will offer insights into additive manufacturing technologies and their applications across industries. Global experts will discuss advances and solutions driving Industry 4.0. Why it matters: The event highlights the UAE's growing focus on advanced manufacturing and its potential to become a hub for additive manufacturing technologies in the region.
DERC is partnering with EPFL in Switzerland on a four-year project using EMTR and ML to study electromagnetic disturbance localization in PCBs. Professor Farhad Rachidi (EPFL) and Dr. Nicolas Mora (DERC) will mentor a PhD student. The collaboration builds on prior relationships between DERC researchers and Prof. Rachidi's lab. Why it matters: The partnership strengthens DERC's methodological expertise and international recognition in electromagnetic studies, potentially leading to further collaborations.
Technology Innovation Institute (TII) and the University of Modena and Reggio Emilia are participating as Team TII-EuroRacing in the Autonomous Challenge at CES 2022 in Las Vegas. TII is also a premier sponsor of the event, which features head-to-head autonomous racecar competition at the Las Vegas Motor Speedway. Team TII-EuroRacing will compete with its DO12 racecar, a Dallara AV-21 retrofitted for automation, after making it to the finals at the Indy Autonomous Challenge in October 2021. Why it matters: This event highlights the UAE's commitment to advancing autonomous robotics and positions TII as a leader in the development of autonomous racing systems.
The Secure Systems Research Center (SSRC) has obtained membership in the seL4 Foundation. This membership allows SSRC to participate in and contribute to the open-source development of seL4, a formally verified microkernel OS. SSRC aims to research, contribute to, and advance next-generation high-end edge device environments using seL4's capabilities. Why it matters: This move enhances the UAE's capabilities in developing secure and resilient edge computing solutions, fostering innovation in critical sectors like secure communications and drone technology.
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.
The Directed Energy Research Center (DERC) is partnering with Montena Technology to study high-altitude electromagnetic pulses and design infrastructure safeguards. DERC is also collaborating with Radaz to evaluate ground penetrating and synthetic aperture radars in Abu Dhabi, aiming to identify natural resources. Additionally, DERC and Université de Picardie Jules Verne are working on laser sources and sensors, with a DERC researcher spending four years in France. Why it matters: These partnerships enhance DERC's research capabilities in critical areas like infrastructure protection, resource exploration, and advanced sensing technologies.
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 Directed Energy Research Center (DERC) has announced partnerships with Ruhr University Bochum, Helmut Schmidt University, University Clermont Auvergne, and National University of Colombia, Bogota. The collaborations aim to advance research in directed energy sub-disciplines, including radar systems, lightning protection, and high-power electromagnetics. These partnerships will involve research on ground-penetrating radar (GPR) and numerical/statistical methods. Why it matters: This international collaboration strengthens the UAE's position as a hub for advanced technology research and development, particularly in the strategic area of directed energy systems.
The Autonomous Robotics Research Center (ARRC) at Abu Dhabi’s Technology Innovation Institute (TII) has appointed a board of advisors composed of globally-recognized experts in robotics and autonomous systems. The advisors include professors from Georgia Tech, ETH Zurich, University of Bologna, Vrije Universiteit Amsterdam, NYU, and Czech Technical University. The board will guide ARRC's research into robotics technologies aimed at building hybrid biological and artificial systems. Why it matters: This signals the UAE's continued investment in attracting top international expertise to advance its AI and robotics research capabilities.
Mae AlMansoori from TII's Directed Energy Research Center won the Young Scientist Award at URSI Kleinheubacher Tagung 2020. Her paper introduced a correlation metric to evaluate the influence of random variables on high-power electromagnetic sources, specifically a Vircator model. The study combined extreme value theory and descriptive statistics to analyze peak output power variability and identify dominant factors. Why it matters: The research offers a framework for managing uncertainties in high-power electromagnetic sources and optimizing their efficiency, relevant for defense and energy applications in the region.
Elon Musk announced that Tesla's project to build a mega AI chip fabrication facility will launch in approximately seven days. The project aims to support Tesla's AI development, particularly for autonomous driving. Tesla has been increasing its investments in AI infrastructure to train large models. Why it matters: This fab could reduce reliance on external chip suppliers and accelerate advancements in self-driving technology in the region and globally.
The Chief of Robo.ai elaborates on why the United Arab Emirates remains a prime location for the development and growth of businesses operating within the 'Machine Economy'. The article likely highlights the supportive regulatory environment, robust infrastructure, and significant investment opportunities available in the UAE. It positions the nation as an ideal hub for AI and robotics startups and established companies seeking to innovate and scale. Why it matters: This perspective underscores the UAE's strategic efforts and success in attracting advanced technology enterprises, reinforcing its ambition to be a global leader in the AI and automation sectors.
The Chief of Robo.ai expressed the view that the United Arab Emirates continues to be an ideal launchpad for the 'Machine Economy'. This perspective likely emphasizes the UAE's robust technological infrastructure, supportive regulatory environment, and strategic government initiatives in advanced technologies. The statement positions the nation as a key global hub for the development and deployment of robotics and artificial intelligence solutions. Why it matters: This highlights the UAE's deliberate efforts to cultivate a competitive ecosystem for emerging technologies and attract international AI and robotics businesses.
HONOR showcased advancements in its AI strategy at MWC 2024, featuring a robot phone concept capable of adapting to user needs and a humanoid robot prototype. The company also introduced the Magic V6, integrating AI for enhanced user experiences. Why it matters: This signals increasing investment and innovation in AI-driven mobile devices from Chinese manufacturers, potentially shaping the future of human-device interaction in the region and globally.
G42 has announced it will be hiring AI agents for certain roles, requiring them to undergo a qualification process and probationary period. The company believes AI agents can enhance efficiency and innovation across various departments. It is unclear which specific roles will be open to AI agents. Why it matters: This move signals a growing acceptance and integration of AI as a workforce component within leading technology companies in the UAE.
The TUM Autonomous Motorsport team developed algorithms and deployment strategies for the Abu Dhabi Autonomous Racing League (A2RL). Their software emulates human driving behavior, pushing vehicle handling and multi-vehicle interactions. The team's approach led to a victory in the A2RL challenge. Why it matters: Autonomous racing serves as a valuable research environment for advancing autonomous driving tech and improving road safety in the region and globally.
The UAE is making significant strides in adopting autonomous systems and future engineering technologies, solidifying its position as a global leader in these fields. This advancement is driven by strategic investments, supportive government policies, and a focus on innovation across various sectors. The nation aims to leverage these technologies to enhance its economic competitiveness and improve the quality of life for its citizens. Why it matters: The UAE's focus on autonomous systems signals a broader regional trend toward embracing advanced technologies for economic diversification and sustainable development.
The Khaleej Times lists the UAE's top 10 AI milestones in 2025, including the planned $500 billion Stargate project focused on advanced technology and the launch of the first tech-driven legal system. Other milestones include advancements in AI-driven healthcare, autonomous vehicles, and sustainable energy solutions. Why it matters: These initiatives signal the UAE's commitment to becoming a global leader in AI innovation and its application across various sectors.
KAUST strengthened Saudi-Italian collaboration in research and innovation during the Saudi-Italian Investment and Business Forum in Riyadh. Three MoUs were signed with Italian academic and industrial institutions, including Politecnico di Torino University and ELT Group. These partnerships will focus on microelectronics, AI, life sciences, robotics, and maritime innovation, alongside a new joint scholarship program. Why it matters: The agreements drive Vision 2030 by expanding international cooperation in key sectors, fostering talent pipelines and technology transfer between Saudi Arabia and Italy.
Teams supported by the Kuwait Foundation for the Advancement of Sciences (KFAS) have successfully qualified for the Robotex competition. Robotex is a global robotics competition that challenges participants in various categories of robot design and programming. This achievement highlights the teams' capabilities in advanced robotics and engineering. Why it matters: This participation demonstrates Kuwait's commitment to fostering STEM education and developing robotics talent among its youth, which is crucial for building a future AI-enabled workforce in the region.
KAUST and SkyGrid are partnering to advance next-generation Advanced Air Mobility (AAM) technologies and operations in Saudi Arabia. They will establish a framework to explore AAM technology, strengthen regulatory readiness, and accelerate Saudi Arabia’s innovation capacity in advanced aviation. Key areas of collaboration include developing an air-side AAM sandbox, flight demonstrations, and R&D in areas like airspace efficiency and UTM automation. Why it matters: This partnership helps position Saudi Arabia at the forefront of Advanced Air Mobility and unlock new economic opportunities in the Kingdom.
KIA, a global automotive company, is joining Brookfield's $10 billion AI investment initiative. The investment will focus on sectors including manufacturing, electric vehicles, and robotics. KIA aims to leverage AI to enhance its automotive technologies and manufacturing processes. Why it matters: This collaboration highlights the increasing interest and investment in AI across diverse sectors in the Middle East, particularly in automotive and manufacturing.
KAUST researchers developed a low-cost, AI-powered drone system to recognize and track camels, addressing challenges faced by local herders. The system uses commercial drones, cameras, and machine learning to monitor camel herds in real time without expensive GPS collars. The AI model revealed insights into camel migration patterns, showing coordinated grazing and sensitivity to drone sounds. Why it matters: This system offers an affordable solution to preserve Saudi Arabia's camel herding tradition while providing valuable insights into camel behavior and contributing to the local economy.
KAUST has launched the Robotics Bay, a 1,000-square-meter interdisciplinary research facility for robotics and autonomous systems. The facility includes a high-bay arena for aerial and ground robot trials, specialized labs, and prototyping tools. It will be used by KAUST faculty, students, collaborators, and national partners to develop and test robotic systems. Why it matters: The new facility strengthens Saudi Arabia's capabilities in robotics and AI, supporting Saudi Vision 2030's goals for economic diversification.
This paper introduces a minimalistic autonomous racing stack designed for high-speed time-trial racing, emphasizing rapid deployment and efficient system integration with minimal on-track testing. Validated on real speedways, the stack achieved a top speed of 206 km/h within just 11 hours of practice, covering 325 km. The system performance analysis includes tracking accuracy, vehicle dynamics, and safety considerations. Why it matters: This research offers insights for teams aiming to quickly develop and deploy autonomous racing stacks with limited track access, potentially accelerating innovation in autonomous vehicle technology within the A2RL and similar racing initiatives.
KAUST and the National Center for Wildlife (NCW) are collaborating on research to protect Saudi Arabia's coastal ecosystems and marine economy from invasive species. They are conducting biodiversity surveys along the Red Sea and Arabian Gulf coasts, having surveyed 34 sites and collected over 10,000 samples. So far, 200 species with potential marine invasive traits have been identified, expanding the national knowledge base of marine life. Why it matters: The partnership aims to develop early detection and monitoring systems, fortifying Saudi Arabia's marine biosecurity efforts and supporting its Vision 2030 blue economy goals.
A research paper proposes a smart waste management system called TUHR for Makkah, Saudi Arabia, leveraging IoT and AI to handle waste accumulation during the annual pilgrimage. The system uses ultrasonic sensors to monitor waste levels and gas detectors to identify harmful substances, alerting authorities when containers are full or hazards are detected. The proposed system aligns with Saudi Vision 2030 by promoting sustainability and improving public health through optimized waste management.
This paper introduces a Bayesian optimization method for estimating tire parameters and their uncertainty, addressing a gap in existing literature. The methodology uses Stochastic Variational Inference to estimate parameters and uncertainties, and it is validated against a Nelder-Mead algorithm. The approach is applied to real-world data from the Abu Dhabi Autonomous Racing League, revealing uncertainties in identifying curvature and shape parameters due to insufficient excitation. Why it matters: The research provides a practical tool for assessing tire model parameters in real-world conditions, with implications for autonomous racing and vehicle dynamics modeling in the GCC region.
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.
This paper introduces a longitudinal control system for autonomous racing vehicles with combustion engines, translating trajectory-tracking commands into low-level vehicle controls like throttle, brake pressure, and gear selection. The modular design facilitates integration with various trajectory-tracking algorithms and vehicles. Experimental validation on the EAV24 racecar during the Abu Dhabi Autonomous Racing League at Yas Marina Circuit demonstrated the system's effectiveness, achieving longitudinal accelerations up to 25 m/s². Why it matters: This research contributes to the advancement of autonomous racing technology in the region, showcasing practical applications in high-performance scenarios and fostering innovation in vehicle control systems.
AlBaik and KAUST have partnered to launch the 'e-AlBaik Lab,' a smart technology living lab on the KAUST campus focused on food service innovation. The collaboration aims to leverage KAUST’s research infrastructure to enhance AlBaik’s food service through automated ordering, smart delivery, and sustainability initiatives. The lab will experiment with technologies like drones and autonomous vehicles to improve delivery efficiency. Why it matters: This partnership signifies the increasing adoption of advanced AI and automation technologies within Saudi Arabia's food industry, potentially setting a precedent for other local businesses to innovate their service and delivery models.
Researchers at KFUPM have developed a system for pothole detection and characterization using a YOLOv8-seg model and depth estimation. A new dataset of images and depth maps was collected from roads in Al-Khobar, Saudi Arabia. The system combines segmentation and depth data to provide a more comprehensive pothole characterization, enhancing autonomous vehicle navigation and road maintenance.
KAUST and the Italian Institute of Technology (IIT) have signed an agreement to collaborate on research in life sciences, AI, robotics, rehabilitation technologies, and nanotechnologies. The partnership will involve joint research projects, academic exchanges, and scientific events. KAUST aims to accelerate innovation and address global challenges by integrating advanced technology and scientific expertise with IIT. Why it matters: This collaboration strengthens KAUST's international research network and supports the development of advanced technologies with potential benefits for Saudi Arabia and the global community.
This paper introduces Arabic language integration into Vision-and-Language Navigation (VLN) in robotics, evaluating multilingual SLMs like GPT-4o mini, Llama 3 8B, Phi-3 14B, and Jais using the NavGPT framework. The study uses the R2R dataset to assess the impact of language on navigation reasoning through zero-shot sequential action prediction. Results show the framework enables high-level planning in both English and Arabic, though some models face challenges with Arabic due to reasoning limitations and parsing issues. Why it matters: This work highlights the need to improve language model planning and reasoning for effective navigation, especially to unlock the potential of Arabic-language models in real-world applications.
Researchers introduce CESAR, a convolutional echo state autoencoder for high-resolution wind forecasting. The model extracts spatial features using a deep convolutional autoencoder and models their dynamics with an echo state network. Tested on high-resolution simulations in Riyadh, Saudi Arabia, CESAR improved wind speed and power forecasting by up to 17% compared to other methods. Why it matters: Accurate wind forecasting is critical for efficient wind farm planning and management in Saudi Arabia and the broader region.
AI technology presents significant opportunities to enhance home safety and security across Saudi Arabia. Potential applications include intelligent surveillance systems, predictive analytics for detecting anomalies, and automated emergency response mechanisms. These solutions aim to provide comprehensive protection for residents against various threats, including intrusions, fires, and other domestic hazards. Why it matters: This highlights Saudi Arabia's proactive approach to adopting advanced AI solutions to improve the quality of life and enhance public safety within its residential communities.
This paper proposes a smart dome model for mosques that uses AI to control dome movements based on weather conditions and overcrowding. The model utilizes Congested Scene Recognition Network (CSRNet) and fuzzy logic techniques in Python to determine when to open and close the domes to maintain fresh air and sunlight. The goal is to automatically manage dome operation based on real-time data, specifying the duration for which the domes should remain open each hour.
KAUST researchers are using black soldier fly (BSF) larvae to transform organic waste into protein-rich animal feed and high-quality organic fertilizer. BSF larvae consume organic matter and reduce waste volume significantly in a 12-day period. Organic Waste Management Solutions (OWMS), a startup launched by the team, is scaling up and commercializing the BSF-based process. Why it matters: This innovative approach offers a sustainable solution for waste management in the region, generating lower carbon emissions compared to existing technologies like incineration and landfilling.
Aitonomi, a company specializing in autonomous EV transport systems, held a recruitment event at KAUST to tap into the university's talent pool. Aitonomi aims to support Saudi Arabia's Vision 2030 by developing fully autonomous and electric transport systems and plans to hire up to 12 skilled workers in KSA for 2024. The company hopes to establish an in-Kingdom manufacturing center and training facility. Why it matters: This initiative highlights the growing demand for AI talent in Saudi Arabia and KAUST's role in supporting the Kingdom's technological advancements and goals for sustainable transportation.
KAUST and McLaren Racing have expanded their 5-year partnership to include collaborative research projects across McLaren's motorsport teams. The partnership will focus on simulation methodologies, optimized computing, and high-efficiency lubricants. KAUST students and researchers will work with McLaren at the McLaren Technology Centre to deliver joint projects. Why it matters: This collaboration provides KAUST students with real-world experience in an applied R&D environment, fostering innovation in areas like materials, lightweight structures, and circularity, with potential implications for the broader automotive and technology sectors in the region.
The paper introduces a framework for camel farm monitoring using a combination of automated annotation and fine-tune distillation. The Unified Auto-Annotation framework uses GroundingDINO and SAM to automatically annotate surveillance video data. The Fine-Tune Distillation framework then fine-tunes student models like YOLOv8, transferring knowledge from a larger teacher model, using data from Al-Marmoom Camel Farm in Dubai.
KAUST's Winter Enrichment Program (WEP) 2024 focused on the theme "Digital Adventure – ride to the future," featuring lectures and activities related to machine learning, AI, and the future of technology. Speakers covered topics from quantum computing and robotics to smart cities and sustainable economies. Rick Fox discussed his company Partanna's work on revolutionizing concrete production with KAUST's Carlos Duarte as an advisor. Why it matters: The event highlights KAUST's role in fostering discussions around cutting-edge technologies and their impact on various sectors within the Kingdom and globally.
KAUST Professor Matteo Parsani will undertake a 30-day, 3000km hand bike journey across Saudi Arabia starting December 17. The journey aims to promote physical activity, raise disability awareness, showcase KAUST research, and highlight Saudi's beauty. KAUST researchers developed biosensor-embedded gear to monitor Parsani's health metrics like heart rate, dopamine levels, and sweat rate during the journey. Why it matters: The initiative demonstrates KAUST's commitment to assistive technology research and promoting inclusivity in Saudi society through adaptive sports.
The Communications and Computing Systems Lab (CCSL) at KAUST received two awards in the International Telecommunication Union AI for Good Machine Learning Challenge and tinyML Hackathon Challenge 2023: Pedestrian Detection. The KAUST team's solution achieved high accuracy in pedestrian identification using event-based cameras, while consuming less power and achieving lower latency. They also received an award for innovative use of "Edge Impulse" for building datasets and training models. Why it matters: This recognition highlights KAUST's growing influence in AI research, particularly in edge computing and computer vision applications for public safety.
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.
This paper introduces a virtual wheel-terrain interaction model developed and validated for the UAE Rashid rover to enhance simulation accuracy for space rovers. The model incorporates wheel grouser properties, slippage, soil properties, and interaction mechanics, validated via lunar soil simulation. Experiments tested a Grouser-Rashid rover wheel at slip ratios of 0, 0.25, 0.50, and 0.75. Why it matters: This simulation method advances rover design and control, crucial for the UAE's space exploration program and lunar mission success.
Researchers at KAUST have developed a new method called Deep State Identifier for extracting information from videos for reinforcement learning. The method learns to predict returns from video-encoded episodes and identifies critical states using mask-based sensitivity analysis. Experiments demonstrate the method's potential for understanding and improving agent behavior in DRL.