KAIST

< Photo 1. A group photo of the research team > Hoverbike is a kind of next-generation mobility that can complement the existing transportation system and can be used as an air transportation means without traffic congestion through high-weight payloads and long-distance flights. It is expected that domestic researchers will contribute to the development of the domestic PAV* and UAM markets by developing a domestically developed manned/unmanned hybrid aircraft that escapes dependence on foreign technology through the development of a high-performance hoverbike. *PAV: Personal Aerial Vehicle. It is a key element of future urban air mobility (UAM, Urban Air Mobility) and constitutes an important part of the next-generation transportation system. KAIST (President Kwang-Hyung Lee) announced on the 27th of December that the research team of Professor Hyochoong Bang of the Department of Aerospace Engineering successfully developed the core technology of a highly reliable multipurpose vertical takeoff and landing hoverbike that can be operated by both manned and unmanned vehicles. This research was participated by the research teams of Professor Jae-Hung Han, Professor Ji-yun Lee, Professor Jae-myung Ahn, Professor Han-Lim Choi, and Professor Chang-Hun Lee of the Department of Aerospace Engineering at KAIST, Professor Dongjin Lee of the Department of Unmanned Aerial Vehicles at Hanseo University, and Professor Jong-Oh Park of the Department of Electronics Engineering at Dong-A University. The research team secured key technologies related to the optimal design of a multipurpose aircraft, hybrid propulsion system, highly reliable precision navigation and flight control system, autonomous flight, and fault detection for the development of a high-performance hoverbike. < Figure 1. Key features of high-reliability multi-purpose hoverbike > The hoverbike platform introduced a gasoline engine-based hybrid system to overcome the shortcomings of battery-based drones, achieving approximately 60% better performance and maximum payload weight compared to overseas technology levels. Through this, it is expected to be utilized in various fields such as emergency supply delivery, logistics, and rescue activities for civilian use, and military transport and mission support for military use. The navigation system was applied by implementing multi-sensor fusion technology based on DGPS/INS* to enable stable flight even in environments without GPS or with weak signals using high-reliability precision navigation technology. *DGPS/INS: Navigation solution combining high accuracy of Differential GPS (DGPS) and Inertial Navigation System (INS) In addition, high-reliability flight control technology was developed to enable reliable maneuvering even under external factors such as payload and wind, and model uncertainty, and fault detection technology was also developed. A guidance technique to automatically land on a helipad after selecting a safe automatic landing area by configuring a high-reliability autonomous flight system was implemented with high accuracy. Stable operation is possible even in complex environments through obstacle avoidance and automatic landing autonomous flight technology. < Figure 2. Hoverbike prototype model > Professor Hyochoong Bang, the research director, emphasized, “We have proven the high practicality of the hoverbike in various environments through high-reliability flight control and precision navigation technology.” He added, “The hoverbike is a promising research result that can not only provide a major path leading to PAVs and future aircraft, but also surpass existing drone technology by several levels. This achievement is even more meaningful because it is the result of five years of effort by eight joint research teams, including the project’s practitioners, PhD students Kwangwoo Jang and Hyungjoo Ahn.”  This study aims to secure core technologies for manned/unmanned multipurpose hoverbikes that can be utilized as new concept aircraft in the defense and civilian sectors. It started as the Defense Acquisition Program Administration’s Defense Technology for Future Challenge Research and Development Project in 2019 and was completed in 2024 under the management of the Agency for Defense Development. It is scheduled to be exhibited for the first time at the 2025 Drone Show Korea (DSK2025), which will be held at BEXCO in Busan from February 26 to 28, 2025.

Despite the development of numerous cancer treatment technologies, the common goal of current cancer therapies is to eliminate cancer cells. This approach, however, faces fundamental limitations, including cancer cells developing resistance and returning, as well as severe side effects from the destruction of healthy cells. < (From top left) Bio and Brain Engineering PhD candidates Juhee Kim, Jeong-Ryeol Gong, Chun-Kyung Lee, and Hoon-Min Kim posed for a group photo with Professor Kwang-Hyun Cho > KAIST (represented by President Kwang Hyung Lee) announced on the 20th of December that a research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering has developed a groundbreaking technology that can treat colon cancer by converting cancer cells into a state resembling normal colon cells without killing them, thus avoiding side effects. The research team focused on the observation that during the oncogenesis process, normal cells regress along their differentiation trajectory. Building on this insight, they developed a technology to create a digital twin of the gene network associated with the differentiation trajectory of normal cells. < Figure 1. Technology for creating a digital twin of a gene network from single-cell transcriptome data of a normal cell differentiation trajectory. Professor Kwang-Hyun Cho's research team developed a digital twin creation technology that precisely observes the dynamics of gene regulatory relationships during the process of normal cells differentiating along a differentiation trajectory and analyzes the relationships among key genes to build a mathematical model that can be simulated (A-F). In addition, they developed a technology to discover key regulatory factors that control the differentiation trajectory of normal cells by simulating and analyzing this digital twin. > < Figure 2. Digital twin simulation simulating the differentiation trajectory of normal colon cells. The dynamics of single-cell transcriptome data for the differentiation trajectory of normal colon cells were analyzed (A) and a digital twin of the gene network was developed representing the regulatory relationships of key genes in this differentiation trajectory (B). The simulation results of the digital twin confirm that it readily reproduces the dynamics of single-cell transcriptome data (C, D). > Through simulation analysis, the team systematically identified master molecular switches that induce normal cell differentiation. When these switches were applied to colon cancer cells, the cancer cells reverted to a normal-like state, a result confirmed through molecular and cellular experiments as well as animal studies. < Figure 3. Discovery of top-level key control factors that induce differentiation of normal colon cells. By applying control factor discovery technology to the digital twin model, three genes, HDAC2, FOXA2, and MYB, were discovered as key control factors that induce differentiation of normal colon cells (A, B). The results of simulation analysis of the regulatory effects of the discovered control factors through the digital twin confirmed that they could induce complete differentiation of colon cells (C). > < Figure 4. Verification of the effect of the key control factors discovered using colon cancer cells and animal experiments on the reversibility of colon cancer. The key control factors of the normal colon cell differentiation trajectory discovered through digital twin simulation analysis were applied to actual colon cancer cells and colon cancer mouse animal models to experimentally verify the effect of cancer reversibility. The key control factors significantly reduced the proliferation of three colon cancer cell lines (A), and this was confirmed in the same way in animal models (B-D). > This research demonstrates that cancer cell reversion can be systematically achieved by analyzing and utilizing the digital twin of the cancer cell gene network, rather than relying on serendipitous discoveries. The findings hold significant promise for developing reversible cancer therapies that can be applied to various types of cancer. < Figure 5. The change in overall gene expression was confirmed through the regulation of the identified key regulatory factors, which converted the state of colon cancer cells to that of normal colon cells. The transcriptomes of colon cancer tissues and normal colon tissues from more than 400 colon cancer patients were compared with the transcriptomes of colon cancer cell lines and reversible colon cancer cell lines, respectively. The comparison results confirmed that the regulation of the identified key regulatory factors converted all three colon cancer cell lines to a state similar to the transcriptome expression of normal colon tissues. > Professor Kwang-Hyun Cho remarked, "The fact that cancer cells can be converted back to normal cells is an astonishing phenomenon. This study proves that such reversion can be systematically induced." He further emphasized, "This research introduces the novel concept of reversible cancer therapy by reverting cancer cells to normal cells. It also develops foundational technology for identifying targets for cancer reversion through the systematic analysis of normal cell differentiation trajectories." This research included contributions from Jeong-Ryeol Gong, Chun-Kyung Lee, Hoon-Min Kim, Juhee Kim, and Jaeog Jeon, and was published in the online edition of the international journal Advanced Science by Wiley on December 11. (Title: “Control of Cellular Differentiation Trajectories for Cancer Reversion”) DOI: https://doi.org/10.1002/advs.202402132 < Figure 6. Schematic diagram of the research results. Professor Kwang-Hyun Cho's research team developed a source technology to systematically discover key control factors that can induce reversibility of colon cancer cells through a systems biology approach and a digital twin simulation analysis of the differentiation trajectory of normal colon cells, and verified the effects of reversion on actual colon cancer through molecular cell experiments and animal experiments. > The study was supported by the Ministry of Science and ICT and the National Research Foundation of Korea through the Mid-Career Researcher Program and Basic Research Laboratory Program. The research findings have been transferred to BioRevert Inc., where they will be used for the development of practical cancer reversion therapies.

The human brain begins learning through spontaneous random activities even before it receives sensory information from the external world. The technology developed by the KAIST research team enables much faster and more accurate learning when exposed to actual data by pre-learning random information in a brain-mimicking artificial neural network, and is expected to be a breakthrough in the development of brain-based artificial intelligence and neuromorphic computing technology in the future. KAIST (President Kwang-Hyung Lee) announced on the 16th of December that Professor Se-Bum Paik 's research team in the Department of Brain Cognitive Sciences solved the weight transport problem*, a long-standing challenge in neural network learning, and through this, explained the principles that enable resource-efficient learning in biological brain neural networks.  *Weight transport problem: This is the biggest obstacle to the development of artificial intelligence that mimics the biological brain. It is the fundamental reason why large-scale memory and computational work are required in the learning of general artificial neural networks, unlike biological brains. Over the past several decades, the development of artificial intelligence has been based on error backpropagation learning proposed by Geoffery Hinton, who won the Nobel Prize in Physics this year. However, error backpropagation learning was thought to be impossible in biological brains because it requires the unrealistic assumption that individual neurons must know all the connected information across multiple layers in order to calculate the error signal for learning. < Figure 1. Illustration depicting the method of random noise training and its effects > This difficult problem, called the weight transport problem, was raised by Francis Crick, who won the Nobel Prize in Physiology or Medicine for the discovery of the structure of DNA, after the error backpropagation learning was proposed by Hinton in 1986. Since then, it has been considered the reason why the operating principles of natural neural networks and artificial neural networks will forever be fundamentally different. At the borderline of artificial intelligence and neuroscience, researchers including Hinton have continued to attempt to create biologically plausible models that can implement the learning principles of the brain by solving the weight transport problem. In 2016, a joint research team from Oxford University and DeepMind in the UK first proposed the concept of error backpropagation learning being possible without weight transport, drawing attention from the academic world. However, biologically plausible error backpropagation learning without weight transport was inefficient, with slow learning speeds and low accuracy, making it difficult to apply in reality. KAIST research team noted that the biological brain begins learning through internal spontaneous random neural activity even before experiencing external sensory experiences. To mimic this, the research team pre-trained a biologically plausible neural network without weight transport with meaningless random information (random noise). As a result, they showed that the symmetry of the forward and backward neural cell connections of the neural network, which is an essential condition for error backpropagation learning, can be created. In other words, learning without weight transport is possible through random pre-training. < Figure 2. Illustration depicting the meta-learning effect of random noise training > The research team revealed that learning random information before learning actual data has the property of meta-learning, which is ‘learning how to learn.’ It was shown that neural networks that pre-learned random noise perform much faster and more accurate learning when exposed to actual data, and can achieve high learning efficiency without weight transport. < Figure 3. Illustration depicting research on understanding the brain's operating principles through artificial neural networks > Professor Se-Bum Paik said, “It breaks the conventional understanding of existing machine learning that only data learning is important, and provides a new perspective that focuses on the neuroscience principles of creating appropriate conditions before learning,” and added, “It is significant in that it solves important problems in artificial neural network learning through clues from developmental neuroscience, and at the same time provides insight into the brain’s learning principles through artificial neural network models.” This study, in which Jeonghwan Cheon, a Master’s candidate of KAIST Department of Brain and Cognitive Sciences participated as the first author and Professor Sang Wan Lee of the same department as a co-author, was presented at the 38th Neural Information Processing Systems (NeurIPS), the world's top artificial intelligence conference, on December 14th in Vancouver, Canada. (Paper title: Pretraining with random noise for fast and robust learning without weight transport) This study was conducted with the support of the National Research Foundation of Korea's Basic Research Program in Science and Engineering, the Information and Communications Technology Planning and Evaluation Institute's Talent Development Program, and the KAIST Singularity Professor Program.

Lithium metal, a next-generation anode material, has been highlighted for overcoming the performance limitations of commercial batteries. However, issues inherent to lithium metal have caused shortened battery lifespans and increased fire risks. KAIST researchers have achieved a world-class breakthrough by extending the lifespan of lithium metal anodes by approximately 750% only using water. KAIST (represented by President Kwang Hyung Lee) announced on the 2nd of December that Professor Il-Doo Kim from the Department of Materials Science and Engineering, in collaboration with Professor Jiyoung Lee from Ajou University, successfully stabilized lithium growth and significantly enhanced the lifespan of next-generation lithium metal batteries using eco-friendly hollow nanofibers as protective layers. Conventional protective layer technologies, which involve applying a surface coating onto lithium metal in order to create an artificial interface with the electrolyte, have relied on toxic processes and expensive materials, with limited improvements in the lifespan of lithium metal anodes. < Figure 1. Schematic illustration of the fabrication process of the newly developed protective membrane by eco-friendly electrospinning process using water > To address these limitations, Professor Kim’s team proposed a hollow nanofiber protective layer capable of controlling lithium-ion growth through both physical and chemical means. This protective layer was manufactured through an environmentally friendly electrospinning process* using guar gum** extracted from plants as the primary material and utilizing water as the sole solvent. *Electrospinning process: A method where polymer solutions are subjected to an electric field, producing continuous fibers with diameters ranging from tens of nanometers to several micrometers. **Guar gum: A natural polymer extracted from guar beans, composed mainly of monosaccharides. Its oxidized functional groups regulate interactions with lithium ions. < Figure 2. Physical and chemical control of Lithium dendrite by the newly developed protective membrane > The nanofiber protective layer effectively controlled reversible chemical reactions between the electrolyte and lithium ions. The hollow spaces within the fibers suppressed the random accumulation of lithium ions on the metal surface, stabilizing the interface between the lithium metal surface and the electrolyte. < Figure 3. Performance of Lithium metal battery full cells with the newly developed protective membrane > As a result, the lithium metal anodes with this protective layer demonstrated approximately a 750% increase in lifespan compared to conventional lithium metal anodes. The battery retained 93.3% of its capacity even after 300 charge-discharge cycles, achieving world-class performance. The researchers also verified that this natural protective layer decomposes entirely within about a month in soil, proving its eco-friendly nature throughout the manufacturing and disposal process. < Figure 4. Excellent decomposition rate of the newly developed protective membrane > Professor Il-Doo Kim explained, “By leveraging both physical and chemical protective functions, we were able to guide reversible reactions between lithium metal and the electrolyte more effectively and suppress dendrite growth, resulting in lithium metal anodes with unprecedented lifespan characteristics.” He added, “As the environmental burden caused by battery production and disposal becomes a pressing issue due to surging battery demand, this water-based manufacturing method with biodegradable properties will significantly contribute to the commercialization of next-generation eco-friendly batteries.” This study was led by Dr. Jiyoung Lee (now a professor in the Department of Chemical Engineering at Ajou University) and Dr. Hyunsub Song (currently at Samsung Electronics), both graduates of KAIST’s Department of Materials Science and Engineering. The findings were published as a front cover article in Advanced Materials, Volume 36, Issue 47, on November 21. (Paper title: “Overcoming Chemical and Mechanical Instabilities in Lithium Metal Anodes with Sustainable and Eco-Friendly Artificial SEI Layer”) The research was supported by the KAIST-LG Energy Solution Frontier Research Lab (FRL), the Alchemist Project funded by the Ministry of Trade, Industry and Energy, and the Top-Tier Research Support Program from the Ministry of Science and ICT.

A Korean research team, which had previously visualized and scientifically proven the harmful effects of carbonated drinks like cola on dental health using nanotechnology, has now identified a mechanism for an effective method to prevent tooth damage caused by these beverages. KAIST (represented by President Kwang Hyung Lee) announced on the 5th of December that a team led by Professor Seungbum Hong from the Department of Materials Science and Engineering, in collaboration with Seoul National University's School of Dentistry (Departments of Pediatric Dentistry and Oral Microbiology) and Professor Hye Ryung Byon’s research team from the Department of Chemistry, has revealed through nanotechnology that silver diamine fluoride (SDF)* forms a fluoride-containing protective layer on the tooth surface, effectively inhibiting cola-induced erosion. *SDF (Silver Diamine Fluoride): A dental agent primarily used for the treatment and prevention of tooth decay. SDF strengthens carious lesions, suppresses bacterial growth, and halts the progression of cavities. The team analyzed the surface morphology and mechanical properties of tooth enamel on a nanoscale using atomic force microscopy (AFM). They also examined the chemical properties of the nano-film formed by SDF treatment using X-ray photoelectron spectroscopy (XPS)* and Fourier-transform infrared spectroscopy (FTIR)*. *XPS (X-ray Photoelectron Spectroscopy): A powerful surface analysis technique used to investigate the chemical composition and electronic structure of materials. *FTIR (Fourier-Transform Infrared Spectroscopy): An analytical method that identifies the molecular structure and composition of materials by analyzing how they absorb or transmit infrared light. The findings showed significant differences in surface roughness and elastic modulus between teeth exposed to cola with and without SDF treatment. Teeth treated with SDF exhibited minimal changes in surface roughness due to erosion (from 64 nm to 70 nm) and maintained a high elastic modulus (from 215 GPa to 205 GPa). This was attributed to the formation of a fluoroapatite* layer by SDF, which acted as a protective shield. *Fluoroapatite: A phosphate mineral with the chemical formula Ca₅(PO₄)₃F (calcium fluoro-phosphate). It can occur naturally or be synthesized biologically/artificially and plays a crucial role in strengthening teeth and bones. < Figure 1. Schematic of the workflow. Surface morphology and mechanical properties of untreated and treated silver diamine fluoride (SDF) treated enamel exposed to cola were analyzed over time using atomic force microscopy (AFM). > Professor Young J. Kim from Seoul National University's Department of Pediatric Dentistry noted, "This technology could be applied to prevent dental erosion and strengthen teeth for both children and adults. It is a cost-effective and accessible dental treatment." < Figure 2. Changes in surface roughness and elastic modulus according to time of exposure to cola for SDF untreated and treated teeth. After 1 hour, the surface roughness of the SDF untreated teeth rapidly became rougher from 83 nm to 287 nm and the elastic modulus weakened from 125 GPa to 13 GPa, whereas the surface roughness of the SDF treated teeth changed only slightly from 64 nm to 70 nm and the elastic modulus barely changed from 215 GPa to 205 GPa, maintaining a similar state to the initial state. > Professor Seungbum Hong emphasized, "Dental health significantly impacts quality of life. This research offers an effective non-invasive method to prevent early dental erosion, moving beyond traditional surgical treatments. By simply applying SDF, dental erosion can be prevented and enamel strengthened, potentially reducing pain and costs associated with treatment." This study, led by the first author Aditi Saha, a PhD student in KAIST’s Department of Materials Science and Engineering, was published in the international journal Biomaterials Research on November 7 under the title "Nanoscale Study on Noninvasive Prevention of Dental Erosion of Enamel by Silver Diamine Fluoride". The research was supported by the National Research Foundation of Korea.

- At the “25th Software Industry Day” celebration held in the afternoon on Monday, December 2nd, 2024 at Yangjae L Tower in Seoul - KAIST was awarded the “Presidential Commendation” for its contributions for the advancement of the Software Industry in the Group Category - Korea’s first AI master’s and doctoral degree program opened at KAIST Kim Jaechul Graduate School of AI - Focus on training non-major developers through SW Officer Training Academy "Jungle", Machine Learning Engineer Bootcamp, etc., talents who can integrate development and collaboration, and advanced talents in the latest AI technologies.  - Professor Minjoon Seo of KAIST Kim Jaechul Graduate School of AI received Prime Minister’s Commendation for his contributions for the advancement of the software industry. < Photo 1. Professor Kyung-soo Kim, the Senior Vice President for Planning and Budget (second from the left) and the Manager of Planning Team, Mr. Sunghoon Jung, stand at the stage after receiving the Presidential Commendation as KAIST was selected as one of the groups that contributed to the advancement of the software industry at the "25th Software Industry Day" celebration. >  “KAIST has been leading the way in achieving the grand goal of fostering 1 million AI talents in Korea by services that pan from providing various educational opportunities, from developing the capabilities of experts with no computer science specialty to fostering advanced professionals. I would like to thank all members of KAIST community who worked hard to achieve the great feat of receiving the Presidential Commendations.” (KAIST President Kwang Hyung Lee) KAIST (President Kwang Hyung Lee) announced on December 3rd that it was selected as a group that contributed to the advancement of the software industry at the “2024 Software Industry Day” celebration held at the Yangjae El Tower in Seoul on the 2nd of December and received a presidential commendation. The “Software Industry Day”, hosted by the Ministry of Science and ICT and organized by the National IT Industry Promotion Agency and the Korea Software Industry Association, is an event designed to promote the status of software industry workers in Korea and to honor their achievements. Every year, those who have made significant contributions to policy development, human resource development, and export growth for industry revitalization are selected and awarded the ‘Software Industry Development Contribution Award.’ KAIST was recognized for its contribution to developing a demand-based, industrial field-centric curriculum and fostering non-major developers and convergence talents with the goal of expanding software value and fostering excellent human resources. < Photo 2. Senior Vice President for Planning and Budget Kyung-soo Kim receiving the commendation as the representative of KAIST > Specifically, it first opened the SW Officer Training Academy "Jungle" to foster convergent program developers equipped with the abilities to handle both the computer coding and human interactions for collaborations. This is a non-degree program that provides intensive study and assignments for 5 months for graduates and intellectuals without prior knowledge of computer science. KAIST Kim Jaechul Graduate School of AI opened and operated Korea’s first master's and doctoral degree program in the field of artificial intelligence. In addition, it planned a “Machine Learning Engineers’ Boot Camp” and conducted lectures and practical training for a total of 16 weeks on the latest AI technologies such as deep learning basics and large language models. It aims to strengthen the practical capabilities of start-up companies while lowering the threshold for companies to introduce AI technology. Also, KAIST was selected to participate in the 1st and 2nd stages of the Software-centered University Project and has been taking part in the project since 2016. Through this, it was highly evaluated for promoting curriculum based on latest technology, an autonomous system where students directly select integrated education, and expansion of internships. < Photo 3. Professor Minjoon Seo of Kim Jaechul Graduate School of AI, who received the Prime Minister's Commendation for his contribution to the advancement of the software industry on the same day > At the awards ceremony that day, Professor Minjoon Seo of KAIST Kim Jaechul Graduate School of AI also received the Prime Minister's Commendation for his contribution to the advancement of the software industry. Professor Seo was recognized for his leading research achievements in the fields of AI and natural language processing by publishing 28 papers in top international AI conferences over the past four years. At the same time, he was noted for his contributions to enhancing the originality and innovation of language model research, such as △knowledge encoding, △knowledge access and utilization, and △high-dimensional inference performance, and for demonstrating leadership in the international academic community. President Kwang Hyung Lee of KAIST stated, “Our university will continue to do its best to foster software talents with global competitiveness through continuous development of cutting-edge curriculum and innovative degree systems.” 

< Photo of ImpriMed CEO Sungwon Lim’s lecture > The Office of Global Initiative at KAIST successfully hosted the 2024 Global Startup Internship Seminar (GSIS) from Wednesday, November 20, to Friday, November 22. Now in its third year, following the 2022 Global Startup Internship Fair, the GSIS aims to introduce KAIST students to internship opportunities at U.S.-based startups and encourage participation in global internship programs, particularly for students with entrepreneurial aspirations. This year’s seminar featured notable startups including ImpriMed, a precision medical AI company; Klleon, an AI culture tech firm; and Bear Robotics, renowned for its autonomous serving robots. Approximately 80 KAIST students attended the event through prior registration. A key highlight of this year’s seminar was the participation of the CEOs from Bear Robotics and ImpriMed, two prominent Silicon Valley startups. Both CEOs, who had previously participated in the 2024 Global Entrepreneurship Summer School (GESS) last June, offered insights into their companies, provided one-on-one career counseling sessions, and discussed the concept of global entrepreneurship with students interested in U.S. startup internships. In addition to company presentations, the seminar offered practical workshops on resume and email writing tailored for U.S. internships, testimonials from current KAIST students and alumni who interned at Silicon Valley startups, and a J1 Visa Information Session, all aimed at preparing students for internships in the United States. So Young Kim, Vice President of the International Office and Director of the Office of Global Initiative, expressed her hopes for the event, stating, “through this event, KAIST students will be inspired by the global entrepreneurial spirit of mentors who have started businesses abroad, and that it will help further spread a culture of challenging adversity and overcoming the risks of failure.” She further added that KAIST is committed to continuously developing programs that cultivate a global entrepreneurial mindset among its students. The 2024 Global Startup Internship Seminar successfully concluded, providing KAIST students with vision and opportunities in global entrepreneurship.

KAIST's quadrupedal walking robot "RAIBO", which can run seamlessly on sandy beaches, has now evolved into "RAIBO2"and achieved the groundbreaking milestone by becomeing the world's first quadrupedal robot to successfully complete a full-course marathon in an official event. < Photo 1. A group photo of RAIBO2 and the team after completing the full-course marathon > KAIST (President Kwang Hyung Lee) announced on the 17th of November that Professor Je Min Hwangbo's research team of the Department of Mechanical Engineering participated in the 22nd Sangju Dried-Persimmon Marathon and completed the full-course race (42.195 km) with a time of 4 hours 19 minutes and 52 seconds. < Photo 2. RAIBO2 after completing the full-course marathon with its official record presented on the photo wall > The Sangju Dried Persimmon Marathon is known for its challenging course featuring two 50 m elevation climbs, each at the 14 km and 28 km marks, making it defficult for amateur runners. This made it an especially demanding challenge for the walking robot, as unexpected losses in efficiency could occur. < Photo 3. RAIBO2 with the completion medal around its neck > To prepare RAIBO2, Professor Hwangbo's team developed a walking controller using reinforcement learning algorithms within their proprietary simulation environment "RaiSim". This simulator allowed the team to simlate diverse terrains such as slopes, stairs, and icy roads to ensure stable walking performance. In particular, RAIBO2's high torque transparency joint mechanism enable the robot to efficiently harvest energy on the downhill slopes to regain some of the energy used in climbing up steep hill. In addition, the stability of the robot was greatly improved through the collaboration with RAION ROBOTICS Inc., a company founded by the researchers from Professor Hwangbo’s lab. < Figure 1. Conceptual diagram of power flow employed by the quadrupedal robot > < Figure 2. The process of leg posture change of RAIBO2 walking at the most efficient walking speed of 3 m/s. By reducing the ground contact speed of the feet, the collision energy loss was reduced, and by minimizing the slipperiness of the foot upon contact, the body's kinetic energy was maintained towards the direction of the movement. > Due to the nature of walking, pedal robots must employ highly complex systems that can withstand periodic vibrations from the frequent impacts that occur upon contact with the ground surface. Immediately after development, high efficiency was already recorded in short-distance experiments in the laboratory at the beginning of the year, but the manufacturing technology of RAION ROBOTICS significantly bolstered RAIBO's performance in running safely for a prolonged time of more than 4 hours among random pack of people in an actual marathon. Compared to previous studies on improving walking efficiency, where external parts or software could not be changed and only limited improvements were made in some areas, Professor Hwangbo’s research team cited the fact that they were able to comprehensively solve problems by developing all steps and parts in-house, including mechanism design, electrical design, software, and artificial intelligence, as a key factor in improving efficiency. Following the development of RAIBO1, the research team developed RAIBO2 and optimized all aspects of the robot. In particular, the team integrated the motor driver circuitry directly into the robot to minimize actuator losses and increase the control bandwidth, greatly improving walking efficiency and stability. < Photo 4. RAIBO2 running the full-course marathon along human participants > Choongin Lee, a Ph.D. Student that co-first author of the studies on RAIBO, said, “Through the marathon project, we demonstrated that RAIBO2 has the walking performance to stably execute services such as delivery and patrol in urban environments with many people and random objects,” and “In follow-up research, we will add autonomous navigation functions to RAIBO and strive to achieve the world’s best walking performance in mountainous and disaster environments.” < Photo 5. RAIBO2 and co-first authors of the related research at the Ph.D. program of the Department of Mechanical Engineering at KAIST. (From left) Choongin Lee, Donghoon Youm, and Jeongsoo Park > This research was conducted with the support of Samsung Electronics Future Technology Promotion Center and RAION ROBOTICS Inc.

“RAIBO”, KAIST’s four-legged robot featuring remarkable agility even on challenging terrains like sandy beaches, is now set to be the first in the world to complete a full marathon. < Photo 1. A group photo of the research team of Professor Je Min Hwangbo (second from the right in the front row) of the Department of Mechanical Engineering who participated in the marathon event at 2024 Geumsan Insam Festival last September > On the 17th of November, KAIST (represented by President Kwang Hyung Lee) announced that Professor Je Min Hwangbo’s team from the Department of Mechanical Engineering has developed an upgraded version, “RAIBO2,” which will take on the full 42.195-kilometer course at the "Sangju Dried-Persimmon Marathon". This is over double the previous maximum distance achieved by quadruped robots, which was limited to around 20 kilometers. The KAIST team has successfully developed a robot that can walk continuously for 43 kilometers on a single charge, completing the course in 4 hours and 40 minutes by following a GPS-guided path on the university’s main athletic field. Through this marathon, the team aims to demonstrate RAIBO2’s walking performance in an actual urban environment. Previously, most measurements of walking robots’ travel distances were confined to controlled laboratory conditions or theoretical data. This marathon challenge is thus significant in that the robot will run alongside the general public in a real urban setting, marking the first attempt to validate the practical potential of four-legged robots in real environments.  Quadruped robots have shown advantages in challenging terrains, such as ice, sand, and mountainous areas, where they can walk stably. However, limited travel distance and running time have long been obstacles to wider applications. < Figure 1. Conceptual diagram of power flow employed by the quadruped robot > Professor Hwangbo’s team designed every component of the robot, from its actuators to its mechanical structure, to overcome these limitations. Notably, they implemented an efficient walking control system based on reinforcement learning using their proprietary dynamic simulator “RaiSim”. The team also collected and analyzed walking data from outdoor environments, creating a model to address walking losses. This model was then used to iteratively improve walking efficiency over one full year. < Figure 2. The leg posture change process of RAIBO2 walking at the most efficient walking speed of 3 m/s. By reducing the ground contact speed of the feet, the collision energy loss was reduced, and by minimizing the slipperiness of the foot upon contact, the body's kinetic energy was maintained towards the direction of the movement. > This is the team’s second attempt. Their first was during the marathon event at “Geumsan Insam Festival” in September when the robot’s battery ran out at the 37-kilometer mark, falling short of completion. The battery drained 10 kilometers earlier than expected due to frequent speed changes as the robot adjusted to the pacing of other runners on the course. Following the initial attempt, the team focused on technical improvements for a successful finish. They enhanced control efficiency by implementing joint stiffness control directly onto the motor actuator and increased battery capacity by 33% by refining the internal structure. These improvements enabled the robot to cover a maximum distance of 67 kilometers on straight paths. < Figure 3. Data from completing 43 km on a single charge at the main sports field on campus. Left) GPS data of the driving course used during autonomous running. Middle) Covered distance by the hour. Right) Energy consumption by module > Choongin Lee, a Ph.D. student of RAI Lab who is one of the co-first author of this study, explained, “Our comprehensive analysis of walking losses in terms of mechanics, electrical systems, and walking methods was crucial to improving walking efficiency. This research marks an important milestone in extending the operating range of quadruped robots to urban environments.” < Photo 2. A Photo from Practice Run> This research was supported by the Samsung Electronics Future Technology Development Center and RAION ROBOTICS Co., Ltd. < Photo 3. A Photo from Practice Run >

< Group photo of our research team participating in the 3rd Cybathlon > The Cybathlon is an international competition, which aims to help overcome disabilities through the use of robotics technology. KAIST researchers came in third, winning the bronze medal, at their 1st participation in 2016, won their first gold medal at the 2nd competition in 2020, and took back the gold medal at this year’s 3rd competition, successfully defending their champion title. KAIST (President Kwang-Hyung Lee) announced on the 28th of October that the wearable robot ‘WalkON Suit F1’ developed by the joint research team of KAIST EXO-Lab, Move Lab, and Angel Robotics, led by Professor Kyoungchul Kong of the Department of Mechanical Engineering (Chairman of Angel Robotics), won gold medal in Cybathlon 2024 held on the 27th. < Seunghwan Kim, the Paraplegic Pilot of Team KAIST, cheering after completing all the missions > Cybathlon is an international competition first held in Switzerland that challenges teams to develop assistive technologies with the purpose of overcoming disabilities, and is also called the Cyborg Olympics. Right after each competition, the missions for the next competition are announced, and research teams from around the world research and develop the right assistive technology for next four years to accomplish the given mission. Aside from the Exoskeleton Race, competitions in a total of eight disciplines are held, including Arm Prosthesis Race, Leg Prosthesis Race, and Wheelchair Race. A total of 71 teams from 26 countries participated in the 3rd Cybathlon event. Professor Kyoungchul Kong’s research team participated in the Exoskeleton Race, the same discipline they took part in the previous competition. The Exoskeleton Race is the highlight of the event that can be called the core of the Cybathlon. In the prosthetic arm or leg events, disabled athletes wearing traditional assistive devices instead of powered devices often win depending more on the ability of the athletes rather than the technology behind the tools. However, the exoskeleton event requires individuals with paraplegic disability to walk completely dependent on the robotic device to perform various missions, so the technical difficulty and the dependence on robotics technology is high. In fact, many teams gave up on participating after seeing the missions for this competition, and more than half of the research teams declared withdrawal during the developmental process. In the end, only six teams from Korea, Thailands, Switzerland, Germany, and the Netherlands participated in the actual competition. Even the research team from the Swiss headquarters declared forfeiture midway as the competition date drew nearer. < Cybathlon 2024 – Exoskeleton Race Mission Description > The reason why many teams gave up in the exoskeleton discipline was because the difficulty of the missions was unusually high. Most research teams have the skills to make paraplegic athletes walk, but there were many other difficult tasks, such as making them walk without crutches or using both hands, while standing free on both legs on the exoskeleton, to cut a lump of sponge block, as in imitating food preparing process. The reason why the difficulty of the missions increased like this is because Professor Kong's research team completed all the missions given to them too quickly in the last competition. In fact, in the last competition, there was even a question asked whether Kim Byeong-Uk (paraplegic) wearing the WalkON Suit F1 was really disabled. Professor Kong's research team developed WalkON Suit F1 to successfully complete the missions. The number of motorized joints increased from six to twelve, and the output of the motor itself was more than doubled compared to the previous model that ran in the competition back in 2020. The 6-channel ground reaction force sensor on the foot measured the robot's balance 1,000 times per second to maintain balance. Cameras were installed to detect obstacles, and an AI board for implementation of AI neural network was also installed. On top of the technologies required to complete the competition missions, a function was implemented that allows the users to wear the robot by themselves and dock on to it right from their wheelchair. In the process, all parts were domestically produced and all basic technologies were internalized. The outer design of the robot was done by Professor Hyunjoon Park of KAIST, and the harmony between people and robots was pursued. In the end, the results of the competition were as expected. The only team that could successfully perform all of the mission tasks, which were originally designed to challenge Professor Kong's research team, was Professor Kong's team. They successfully completed missions such as moving by sidesteps between narrow chairs, moving boxes, walking freely unassisted by crutches, passing through a narrow door and closing it behind, and working on food preparation in the kitchen, recording 6 minutes and 41 seconds to complete all six tasks. The Swiss and Thai teams that took 2nd and 3rd places were all given 10 minutes, but only were able to perform two missions, each earning twenty points. It was an unevenly matched race to begin with. The Cybathlon broadcast team was more surprised and interested in the performance of WalkON Suit F1 than in result of the race. < Team KAIST’s Paraplegic Pilot Seunghwan Kim (left), and Professor Kyoungchul Kong (right) > Researcher Jeongsu Park, the captain of Team KAIST, said, “We came into this competition thinking of it as a competition against ourselves to begin with and focused on showing the technological gap. Now, we are very happy and proud that our endeavors achieved such good result as well.” He added, “We plan to continue to showcase various functions of the WalkON Suit F1 that have not yet been publicly introduced.” Researcher Seunghwan Kim, the paraplegic athlete of the team, said, “I am so touched that I was able to introduce the world’s best wearable robot technology of Korea with my own body.” On a different note, Professor Kong’s research team has successfully commercialized wearable robots through Angel Robotics Co., Ltd. since the 2020 competition. In 2022, they began distributing “ANGEL LEGS M20,” the first wearable robot to be covered by health insurance, and as a result, Angel Robotics Co., Ltd. was successfully listed on KOSDAQ this March. The various know-how and core technologies accumulated while preparing for this competition is to contribute to further development and propagation of wearable robots, provoking imagination to draw on the future of wearable robots and on how it may change our daily lives. Final Match (Self-filmed): https://youtu.be/3ASAtvkiOhw Final Match and Interview (Official Video): https://youtu.be/FSfxOTpDjSE Final Match and Interview (Summary): https://youtu.be/Sb_vd5-3f_0

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