bitsensing, global industry experts in advanced radar solutions, has announced that it has entered into a Memorandum of Understanding (MOU) with the Autonomous Vehicles and Embedded Systems (AVE) Lab at the Korea Advanced Institute of Science and Technology (KAIST) and ZETA Mobility to advance the commercialization of AI-based automotive 4D imaging radar technology.
The MOU brings together leading expertise in radar platform development, AI sensor fusion, and autonomous vehicle data to co-develop a real-time, embedded AI-based solution that enhances the performance of 4D imaging radar—recognized as a critical sensing technology for autonomous driving and Advanced Driver Assistance Systems (ADAS).
bitsensing, KAIST AVE Lab, and ZETA Mobility have signed a strategic MOU to co-develop AI-powered 4D imaging radar for next-gen automotive perception systems.
Under the agreement, bitsensing will supply its proprietary high-performance 4D imaging radar hardware platform. KAIST AVE Lab will contribute advanced AI algorithms based on radar signal processing and sensor fusion. ZETA Mobility will provide embedded AI development expertise and access to large-scale automotive datasets. The goal is to deliver a collaborative, real-time, embedded radar solution that improves perception and safety for autonomous vehicles and ADAS applications.
Unlike conventional radar, 4D imaging radar captures not only distance, velocity, and direction, but also elevation (Z-axis), enabling highly accurate detection and classification of objects in complex environments. With reliable performance even in adverse weather conditions such as rain, fog, and snow, this technology is particularly well suited to the demands of autonomous driving, where safety and reliability are paramount.
Through this collaboration, the partners aim to further advance radar sensing technologies that significantly improve the recognition and classification of vehicles, pedestrians, and infrastructure in real-world automotive environments.
“4D imaging radar is a key sensor for autonomous driving that demands both high precision and all-weather reliability,” said Jae-Eun Lee, CEO of bitsensing. “By combining bitsensing’s proprietary radar expertise with the AI and dataset capabilities of KAIST AVE Lab and ZETA Mobility, we are taking a major step forward in bringing next-generation radar solutions to market.”
Professor Seung-Hyun Kong of the AVE Lab at the Cho Chun Shik Graduate School of Mobility at KAIST said, “This agreement is particularly significant as it represents collaboration among institutions that possess core technologies essential for developing artificial intelligence for 4D radar.” He further added, “Bitsensing, specializing in high-performance 4D radar hardware; ZETA Mobility, developing embedded AI-based data processing and system integration modules; and KAIST AVE Lab, a leading group in AI research for surrounding object recognition using 4D radar, will combine their unique expertise. Through this partnership, we aim to lead the world in developing and commercializing advanced AI-embedded 4D radar systems.”
Hyunseok Lee, CEO of ZETA Mobility, stated, “This partnership, through which specialized institutions collaborate to solve technological challenges and develop world-class solutions, is extremely meaningful. ZETA Mobility will leverage our embedded AI expertise to contribute significantly to advancing and commercializing autonomous driving technologies.”
The three parties plan to engage in phased joint development efforts, including R&D, system validation, field testing, and integration. The collaboration is expected to accelerate the development and deployment of commercially viable 4D imaging radar systems embedded with AI. To learn more, please click here.
About bitsensing
Founded in 2018, bitsensing is a radar technology company focused on developing advanced imaging radar sensors for automotive, industrial, and smart city applications. Its solutions support safe and autonomous mobility through precision sensing, intelligent data interpretation, and seamless hardware integration. The company is headquartered in Seoul, South Korea. For more information, please click here.
About KAIST AVE Lab
The Autonomous Vehicles and Embedded Systems (AVE) Lab at the Cho Chun Shik Graduate School of Mobility at KAIST conducts pioneering research in AI for autonomous driving, radar signal processing, and sensor fusion. It is known for creating the K-Radar dataset and leads international collaborations to advance 4D radar-based perception. For more information, visit https://ave.kaist.ac.kr.
About ZETA Mobility
ZETA Mobility is a South Korean startup specializing in embedded AI systems and 4D radar-based perception technologies for autonomous vehicles. Founded in 2024, the company participates in advanced AI initiatives and collaborates with research institutions to develop open-source mobility platforms. To learn more, please click here.
Source/Photo Credit: bitsensing
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Molly is the Founder, Publisher, and Editor-in-Chief of Components Source Network, the industry’s first and only known 100% woman-owned and woman-led B2B publishing platform serving the global high-tech manufacturing and engineering sectors. Her portfolio includes Sensors + Testing Monthly and ten additional specialized e-news publications. With more than 25 years of experience spanning strategic technical marketing, public relations, and business development in highly specialized technical markets, she also leads Embassy Global, LLC, a virtual consultancy that has supported the growth of more than 200 high-tech industry brands worldwide since 2008. In addition to her publishing and advisory work, Molly has been appointed to serve as Second Vice Chair of the Government Relations Team for the Women’s Business Enterprise National Council (WBENC) Forum, beginning in 2026, supporting policy development and advocacy initiatives advancing women-owned businesses. A long-standing voice for small business, supplier diversity, and women in STEM, she was also a 2025 finalist for the WBEC Metro New York Outstanding Advocate Award. Connect with her on LinkedIn.
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