College+of+Engineering
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KAIST develops 'MetaVRain' that realizes vivid 3D real-life images
KAIST (President Kwang Hyung Lee) is a high-speed, low-power artificial intelligence (AI: Artificial Intelligent) semiconductor* MetaVRain, which implements artificial intelligence-based 3D rendering that can render images close to real life on mobile devices.
* AI semiconductor: Semiconductor equipped with artificial intelligence processing functions such as recognition, reasoning, learning, and judgment, and implemented with optimized technology based on super intelligence, ultra-low power, and ultra-reliability
The artificial intelligence semiconductor developed by the research team makes the existing ray-tracing*-based 3D rendering driven by GPU into artificial intelligence-based 3D rendering on a newly manufactured AI semiconductor, making it a 3D video capture studio that requires enormous costs. is not needed, so the cost of 3D model production can be greatly reduced and the memory used can be reduced by more than 180 times. In particular, the existing 3D graphic editing and design, which used complex software such as Blender, is replaced with simple artificial intelligence learning, so the general public can easily apply and edit the desired style.
* Ray-tracing: Technology that obtains images close to real life by tracing the trajectory of all light rays that change according to the light source, shape and texture of the object
This research, in which doctoral student Donghyun Han participated as the first author, was presented at the International Solid-State Circuit Design Conference (ISSCC) held in San Francisco, USA from February 18th to 22nd by semiconductor researchers from all over the world.
(Paper Number 2.7, Paper Title: MetaVRain: A 133mW Real-time Hyper-realistic 3D NeRF Processor with 1D-2D Hybrid Neural Engines for Metaverse on Mobile Devices (Authors: Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, and Hoi-Jun Yoo))
Professor Yoo's team discovered inefficient operations that occur when implementing 3D rendering through artificial intelligence, and developed a new concept semiconductor that combines human visual recognition methods to reduce them. When a person remembers an object, he has the cognitive ability to immediately guess what the current object looks like based on the process of starting with a rough outline and gradually specifying its shape, and if it is an object he saw right before. In imitation of such a human cognitive process, the newly developed semiconductor adopts an operation method that grasps the rough shape of an object in advance through low-resolution voxels and minimizes the amount of computation required for current rendering based on the result of rendering in the past.
MetaVRain, developed by Professor Yu's team, achieved the world's best performance by developing a state-of-the-art CMOS chip as well as a hardware architecture that mimics the human visual recognition process. MetaVRain is optimized for artificial intelligence-based 3D rendering technology and achieves a rendering speed of up to 100 FPS or more, which is 911 times faster than conventional GPUs. In addition, as a result of the study, the energy efficiency, which represents the energy consumed per video screen processing, is 26,400 times higher than that of GPU, opening the possibility of artificial intelligence-based real-time rendering in VR/AR headsets and mobile devices.
To show an example of using MetaVRain, the research team developed a smart 3D rendering application system together, and showed an example of changing the style of a 3D model according to the user's preferred style. Since you only need to give artificial intelligence an image of the desired style and perform re-learning, you can easily change the style of the 3D model without the help of complicated software. In addition to the example of the application system implemented by Professor Yu's team, it is expected that various application examples will be possible, such as creating a realistic 3D avatar modeled after a user's face, creating 3D models of various structures, and changing the weather according to the film production environment. do.
Starting with MetaVRain, the research team expects that the field of 3D graphics will also begin to be replaced by artificial intelligence, and revealed that the combination of artificial intelligence and 3D graphics is a great technological innovation for the realization of the metaverse.
Professor Hoi-Jun Yoo of the Department of Electrical and Electronic Engineering at KAIST, who led the research, said, “Currently, 3D graphics are focused on depicting what an object looks like, not how people see it.” The significance of this study was revealed as a study that enabled efficient 3D graphics by borrowing the way people recognize and express objects by imitating them.” He also foresaw the future, saying, “The realization of the metaverse will be achieved through innovation in artificial intelligence technology and innovation in artificial intelligence semiconductors, as shown in this study.”
Figure 1. Description of the MetaVRain demo screen
Photo of Presentation at the International Solid-State Circuits Conference (ISSCC)
2023.03.13 View 4717 -
KAIST team develops smart immune system that can pin down on malignant tumors
A joint research team led by Professor Jung Kyoon Choi of the KAIST Department of Bio and Brain Engineering and Professor Jong-Eun Park of the KAIST Graduate School of Medical Science and Engineering (GSMSE) announced the development of the key technologies to treat cancers using smart immune cells designed based on AI and big data analysis. This technology is expected to be a next-generation immunotherapy that allows precision targeting of tumor cells by having the chimeric antigen receptors (CARs) operate through a logical circuit. Professor Hee Jung An of CHA Bundang Medical Center and Professor Hae-Ock Lee of the Catholic University of Korea also participated in this research to contribute joint effort.
Professor Jung Kyoon Choi’s team built a gene expression database from millions of cells, and used this to successfully develop and verify a deep-learning algorithm that could detect the differences in gene expression patterns between tumor cells and normal cells through a logical circuit. CAR immune cells that were fitted with the logic circuits discovered through this methodology could distinguish between tumorous and normal cells as a computer would, and therefore showed potentials to strike only on tumor cells accurately without causing unwanted side effects.
This research, conducted by co-first authors Dr. Joonha Kwon of the KAIST Department of Bio and Brain Engineering and Ph.D. candidate Junho Kang of KAIST GSMSE, was published by Nature Biotechnology on February 16, under the title Single-cell mapping of combinatorial target antigens for CAR switches using logic gates.
An area in cancer research where the most attempts and advances have been made in recent years is immunotherapy. This field of treatment, which utilizes the patient’s own immune system in order to overcome cancer, has several methods including immune checkpoint inhibitors, cancer vaccines and cellular treatments. Immune cells like CAR-T or CAR-NK equipped with chimera antigen receptors, in particular, can recognize cancer antigens and directly destroy cancer cells.
Starting with its success in blood cancer treatment, scientists have been trying to expand the application of CAR cell therapy to treat solid cancer. But there have been difficulties to develop CAR cells with effective killing abilities against solid cancer cells with minimized side effects. Accordingly, in recent years, the development of smarter CAR engineering technologies, i.e., computational logic gates such as AND, OR, and NOT, to effectively target cancer cells has been underway.
At this point in time, the research team built a large-scale database for cancer and normal cells to discover the exact genes that are expressed only from cancer cells at a single-cell level. The team followed this up by developing an AI algorithm that could search for a combination of genes that best distinguishes cancer cells from normal cells. This algorithm, in particular, has been used to find a logic circuit that can specifically target cancer cells through cell-level simulations of all gene combinations. CAR-T cells equipped with logic circuits discovered through this methodology are expected to distinguish cancerous cells from normal cells like computers, thereby minimizing side effects and maximizing the effects of chemotherapy.
Dr. Joonha Kwon, who is the first author of this paper, said, “this research suggests a new method that hasn’t been tried before. What’s particularly noteworthy is the process in which we found the optimal CAR cell circuit through simulations of millions of individual tumors and normal cells.” He added, “This is an innovative technology that can apply AI and computer logic circuits to immune cell engineering. It would contribute greatly to expanding CAR therapy, which is being successfully used for blood cancer, to solid cancers as well.”
This research was funded by the Original Technology Development Project and Research Program for Next Generation Applied Omic of the Korea Research Foundation.
Figure 1. A schematic diagram of manufacturing and administration process of CAR therapy and of cancer cell-specific dual targeting using CAR.
Figure 2. Deep learning (convolutional neural networks, CNNs) algorithm for selection of dual targets based on gene combination (left) and algorithm for calculating expressing cell fractions by gene combination according to logical circuit (right).
2023.03.09 View 6296 -
KAIST presents a fundamental technology to remove metastatic traits from lung cancer cells
KAIST (President Kwang Hyung Lee) announced on January 30th that a research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering succeeded in using systems biology research to change the properties of carcinogenic cells in the lungs and eliminate both drug resistance and their ability to proliferate out to other areas of the body.
As the incidences of cancer increase within aging populations, cancer has become the most lethal disease threatening healthy life. Fatality rates are especially high when early detection does not happen in time and metastasis has occurred in various organs. In order to resolve this problem, a series of attempts were made to remove or lower the ability of cancer cells to spread, but they resulted in cancer cells in the intermediate state becoming more unstable and even more malignant, which created serious treatment challenges.
Professor Kwang-Hyun Cho's research team simulated various cancer cell states in the Epithelial-to-Mesenchymal Transition (EMT) of lung cancer cells, between epithelial cells without metastatic ability and mesenchymal cells with metastatic ability. A mathematical model of molecular network was established, and key regulators that could reverse the state of invasive and drug resistant mesenchymal cells back to the epithelial state were discovered through computer simulation analysis and molecular cell experiments. In particular, this process succeeded in properly reverting the mesenchymal lung cancer cells to a state where they were sensitive to chemotherapy treatment while avoiding the unstable EMT hybrid cell state in the middle process, which had remained a difficult problem.
The results of this research, in which KAIST Ph.D. student Namhee Kim, Dr. Chae Young Hwang, Researcher Taeyoung Kim, and Ph.D. student Hyunjin Kim participated, were published as an online paper in the international journal “Cancer Research” published by the American Association for Cancer Research (AACR) on January 30th. (Paper title: A cell fate reprogramming strategy reverses epithelial-to-mesenchymal transition of lung cancer cells while avoiding hybrid states)
Cells in an EMT hybrid state, which are caused by incomplete transitions during the EMT process in cancer cells, have the characteristics of both epithelial cells and mesenchymal cells, and are known to have high drug resistance and metastatic potential by acquiring high stem cell capacity. In particular, EMT is further enhanced through factors such as transforming growth factor-beta (TGF-β) secreted from the tumor microenvironment (TME) and, as a result, various cell states with high plasticity appear. Due to the complexity of EMT, it has been very difficult to completely reverse the transitional process of the mesenchymal cancer cells to an epithelial cell state in which metastatic ability and drug resistance are eliminated while avoiding the EMT hybrid cell state with high metastatic ability and drug resistance.
Professor Kwang-Hyun Cho's research team established a mathematical model of the gene regulation network that governs the complex process of EMT, and then applied large-scale computer simulation analysis and complex system network control technology to identify and verify 'p53', 'SMAD4', and 'ERK1' and 'ERK 2' (collectively ERKs) through molecular cell experiments as the three key molecular targets that can transform lung cancer cells in the mesenchymal cell state, reversed back to an epithelial cell state that no longer demonstrates the ability to metastasize, while avoiding the EMT hybrid cell state.
In particular, by analyzing the molecular regulatory mechanism of the complex EMT process at the system level, the key pathways were identified that were linked to the positive feedback that plays an important role in completely returning cancer cells to an epithelial cell state in which metastatic ability and drug resistance are removed.
This discovery is significant in that it proved that mesenchymal cells can be reverted to the state of epithelial cells under conditions where TGF-β stimulation are present, like they are in the actual environment where cancer tissue forms in the human body.
Abnormal EMT in cancer cells leads to various malignant traits such as the migration and invasion of cancer cells, changes in responsiveness to chemotherapy treatment, enhanced stem cell function, and the dissemination of cancer. In particular, the acquisition of the metastatic ability of cancer cells is a key determinant factor for the prognosis of cancer patients. The EMT reversal technology in lung cancer cells developed in this research is a new anti-cancer treatment strategy that reprograms cancer cells to eliminate their high plasticity and metastatic potential and increase their responsiveness to chemotherapy.
Professor Kwang-Hyun Cho said, "By succeeding in reversing the state of lung cancer cells that acquired high metastatic traits and resistance to drugs and reverting them to a treatable epithelial cell state with renewed sensitivity to chemotherapy, the research findings propose a new strategy for treatments that can improve the prognosis of cancer patients.”
Professor Kwang-Hyun Cho's research team was the first to present the principle of reversal treatment to revert cancer cells to normal cells, following through with the announcement of the results of their study that reverted colon cancer cells to normal colon cells in January of 2020, and also presenting successful re-programming research where the most malignant basal type breast cancer cells turned into less-malignant luminal type breast cancer cells that were treatable with hormonal therapies in January of 2022. This latest research result is the third in the development of reversal technology where lung cancer cells that had acquired metastatic traits returned to a state in which their metastatic ability was removed and drug sensitivity was enhanced.
This research was carried out with support from the Ministry of Science and ICT and the National Research Foundation of Korea's Basic Research in Science & Engineering Program for Mid-Career Researchers.
< Figure 1. Construction of the mathematical model of the regulatory network to represent the EMT phenotype based on the interaction between various molecules related to EMT.
(A) Professor Kwang-Hyun Cho's research team investigated numerous literatures and databases related to complex EMT, and based on comparative analysis of cell line data showing epithelial and mesenchymal cell conditions, they extracted key signaling pathways related to EMT and built a mathematical model of regulatory network (B) By comparing the results of computer simulation analysis and the molecular cell experiments, it was verified how well the constructed mathematical model simulated the actual cellular phenomena. >
< Figure 2. Understanding of various EMT phenotypes through large-scale computer simulation analysis and complex system network control technology.
(A) Through computer simulation analysis and experiments, Professor Kwang-Hyun Cho's research team found that complete control of EMT is impossible with single-molecule control alone. In particular, through comparison of the relative stability of attractors, it was revealed that the cell state exhibiting EMT hybrid characteristics has unstable properties. (B), (C) Based on these results, Prof. Cho’s team identified two feedbacks (positive feedback consisting of Snail-miR-34 and ZEB1-miR-200) that play an important role in avoiding the EMT hybrid state that appeared in the TGF-β-ON state. It was found through computer simulation analysis that the two feedbacks restore relatively high stability when the excavated p53 and SMAD4 are regulated. In addition, molecular cell experiments demonstrated that the expression levels of E-cad and ZEB1, which are representative phenotypic markers of EMT, changed similarly to the expression profile in the epithelial cell state, despite the TGF-β-ON state. >
< Figure 3. Complex molecular network analysis and discovery of reprogramming molecular targets for intact elimination of EMT hybrid features.
(A) Controlling the expression of p53 and SMAD4 in lung cancer cell lines was expected to overcome drug resistance, but contrary to expectations, chemotherapy responsiveness was not restored. (B) Professor Kwang-Hyun Cho's research team additionally analyzed computer simulations, genome data, and experimental results and found that high expression levels of TWIST1 and EPCAM were related to drug resistance. (C) Prof. Cho’s team identified three key molecular targets: p53, SMAD4 and ERK1 & ERK2. (D), (E) Furthermore, they identified a key pathway that plays an important role in completely reversing into epithelial cells while avoiding EMT hybrid characteristics, and confirmed through network analysis and attractor analysis that high stability of the key pathway was restored when the proposed molecular target was controlled. >
< Figure 4. Verification through experiments with lung cancer cell lines.
When p53 was activated and SMAD4 and ERK1/2 were inhibited in lung cancer cell lines, (A), (B) E-cad protein expression increased and ZEB1 protein expression decreased, and (C) mesenchymal cell status including TWIST1 and EPCAM and gene expression of markers related to stem cell potential characteristics were completely inhibited. In addition, (D) it was confirmed that resistance to chemotherapy treatment was also overcome as the cell state was reversed by the regulated target. >
< Figure 5. A schematic representation of the research results.
Prof. Cho’s research team identified key molecular regulatory pathways to avoid high plasticity formed by abnormal EMT of cancer cells and reverse it to an epithelial cell state through systems biology research. From this analysis, a reprogramming molecular target that can reverse the state of mesenchymal cells with acquired invasiveness and drug resistance to the state of epithelial cells with restored drug responsiveness was discovered.
For lung cancer cells, when a drug that enhances the expression of p53, one of the molecular targets discovered, and inhibits the expression of SMAD4 and ERK1 & ERK2 is administered, the molecular network of genes in the state of mesenchymal cells is modified, eventually eliminating metastatic ability and it is reprogrammed to turn into epithelial cells without the resistance to chemotherapy treatments. >
2023.01.30 View 12039 -
KAIST’s Robo-Dog “RaiBo” runs through the sandy beach
KAIST (President Kwang Hyung Lee) announced on the 25th that a research team led by Professor Jemin Hwangbo of the Department of Mechanical Engineering developed a quadrupedal robot control technology that can walk robustly with agility even in deformable terrain such as sandy beach.
< Photo. RAI Lab Team with Professor Hwangbo in the middle of the back row. >
Professor Hwangbo's research team developed a technology to model the force received by a walking robot on the ground made of granular materials such as sand and simulate it via a quadrupedal robot. Also, the team worked on an artificial neural network structure which is suitable in making real-time decisions needed in adapting to various types of ground without prior information while walking at the same time and applied it on to reinforcement learning. The trained neural network controller is expected to expand the scope of application of quadrupedal walking robots by proving its robustness in changing terrain, such as the ability to move in high-speed even on a sandy beach and walk and turn on soft grounds like an air mattress without losing balance.
This research, with Ph.D. Student Soo-Young Choi of KAIST Department of Mechanical Engineering as the first author, was published in January in the “Science Robotics”. (Paper title: Learning quadrupedal locomotion on deformable terrain).
Reinforcement learning is an AI learning method used to create a machine that collects data on the results of various actions in an arbitrary situation and utilizes that set of data to perform a task. Because the amount of data required for reinforcement learning is so vast, a method of collecting data through simulations that approximates physical phenomena in the real environment is widely used.
In particular, learning-based controllers in the field of walking robots have been applied to real environments after learning through data collected in simulations to successfully perform walking controls in various terrains.
However, since the performance of the learning-based controller rapidly decreases when the actual environment has any discrepancy from the learned simulation environment, it is important to implement an environment similar to the real one in the data collection stage. Therefore, in order to create a learning-based controller that can maintain balance in a deforming terrain, the simulator must provide a similar contact experience.
The research team defined a contact model that predicted the force generated upon contact from the motion dynamics of a walking body based on a ground reaction force model that considered the additional mass effect of granular media defined in previous studies.
Furthermore, by calculating the force generated from one or several contacts at each time step, the deforming terrain was efficiently simulated.
The research team also introduced an artificial neural network structure that implicitly predicts ground characteristics by using a recurrent neural network that analyzes time-series data from the robot's sensors.
The learned controller was mounted on the robot 'RaiBo', which was built hands-on by the research team to show high-speed walking of up to 3.03 m/s on a sandy beach where the robot's feet were completely submerged in the sand. Even when applied to harder grounds, such as grassy fields, and a running track, it was able to run stably by adapting to the characteristics of the ground without any additional programming or revision to the controlling algorithm.
In addition, it rotated with stability at 1.54 rad/s (approximately 90° per second) on an air mattress and demonstrated its quick adaptability even in the situation in which the terrain suddenly turned soft.
The research team demonstrated the importance of providing a suitable contact experience during the learning process by comparison with a controller that assumed the ground to be rigid, and proved that the proposed recurrent neural network modifies the controller's walking method according to the ground properties.
The simulation and learning methodology developed by the research team is expected to contribute to robots performing practical tasks as it expands the range of terrains that various walking robots can operate on.
The first author, Suyoung Choi, said, “It has been shown that providing a learning-based controller with a close contact experience with real deforming ground is essential for application to deforming terrain.” He went on to add that “The proposed controller can be used without prior information on the terrain, so it can be applied to various robot walking studies.”
This research was carried out with the support of the Samsung Research Funding & Incubation Center of Samsung Electronics.
< Figure 1. Adaptability of the proposed controller to various ground environments. The controller learned from a wide range of randomized granular media simulations showed adaptability to various natural and artificial terrains, and demonstrated high-speed walking ability and energy efficiency. >
< Figure 2. Contact model definition for simulation of granular substrates. The research team used a model that considered the additional mass effect for the vertical force and a Coulomb friction model for the horizontal direction while approximating the contact with the granular medium as occurring at a point. Furthermore, a model that simulates the ground resistance that can occur on the side of the foot was introduced and used for simulation. >
2023.01.26 View 11759 -
Overview of the 30-year history of metabolic engineering
< Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST >
A research team comprised of Gi Bae Kim, Dr. So Young Choi, Dr. In Jin Cho, Da-Hee Ahn, and Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST reported the 30-year history of metabolic engineering, highlighting examples of recent progress in the field and contributions to sustainability and health. Their paper “Metabolic engineering for sustainability and health” was published online in the 40th anniversary special issue of Trends in Biotechnology on January 10, 2023.
Metabolic engineering, a discipline of engineering that modifies cell phenotypes through molecular and genetic-level manipulations to improve cellular activities, has been studied since the early 1990s, and has progressed significantly over the past 30 years. In particular, metabolic engineering has enabled the engineering of microorganisms for the development of microbial cell factories capable of efficiently producing chemicals and materials as well as degrading recalcitrant contaminants.
This review article revisited how metabolic engineering has advanced over the past 30 years, from the advent of genetic engineering techniques such as recombinant DNA technologies to recent breakthroughs in systems metabolic engineering and data science aided by artificial intelligence. The research team highlighted momentous events and achievements in metabolic engineering, providing both trends and future directions in the field. Metabolic engineering’s contributions to bio-based sustainable chemicals and clean energy, health, and bioremediation were also reviewed. Finally, the research team shared their perspectives on the future challenges impacting metabolic engineering than must be overcome in order to achieve advancements in sustainability and health.
Distinguished Professor Sang Yup Lee said, “Replacing fossil resource-based chemical processes with bio-based sustainable processes for the production of chemicals, fuels, and materials using metabolic engineering has become our essential task for the future. By looking back on the 30+ years of metabolic engineering, we aimed to highlight the contributions of metabolic engineering to achieve sustainability and good health.” He added, “Metabolic engineering will play an increasingly important role as a key solution to the climate crisis, environmental pollution, food and energy shortages, and health problems in aging societies.”
< Figure: Metabolic Engineering Timeline >
2023.01.25 View 7760 -
KAIST’s unmanned racing car to race in the Indy Autonomous Challenge @ CES 2023 as the only contender representing Asia
- Professor David Hyunchul Shim of the School of Electrical Engineering, is at the Las Vegas Motor Speedway in Las Vegas, Nevada with his students of the Unmanned Systems Research Group (USRG), participating in the Indy Autonomous Challenge (IAC) @ CES as the only Asian team in the race.
Photo 1. Nine teams that competed at the first Indy Autonomous Challenge on October 23, 2021. (KAIST team is the right most team in the front row)
- The EE USRG team won the slot to race in the IAC @ CES 2023 rightly as the semifinals entree of the IAC @ CES 2022’ held in January of last year
- Through the partnership with Hyundai Motor Company, USRG received support to participate in the competition, and is to share the latest developments and trends of the technology with the company researchers
- With upgrades from last year, USRG is to race with a high-speed Indy racing car capable of driving up to 300 km/h and the technology developed in the process is to be used in further advancement of the high-speed autonomous vehicle technology of the future.
KAIST (President Kwang Hyung Lee) announced on the 5th that it will participate in the “Indy Autonomous Challenge (IAC) @ CES 2023”, an official event of the world's largest electronics and information technology exhibition held every year in Las Vegas, Nevada, of the United States from January 5th to 8th.
Photo 2. KAIST Racing Team participating in the Indy Autonomous Challenge @ CES 2023 (Team Leader: Sungwon Na, Team Members: Seongwoo Moon, Hyunwoo Nam, Chanhoe Ryu, Jaeyoung Kang)
“IAC @ CES 2023”, which is to be held at the Las Vegas Motor Speedway (LVMS) on January 7, seeks to advance technology developed as the result of last year's competition to share the results of such advanced high-speed autonomous vehicle technology with the public.
This competition is the 4th competition following the “Indy Autonomous Challenge (IAC)” held for the first time in Indianapolis, USA on October 23, 2021. At the IAC @ CES 2022 following the first IAC competition, the Unmmaned Systems Research Group (USRG) team led by Professor David Hyunchul Shim advanced to the semifinals out of a total of nine teams and won a spot to participate in CES 2023. As a result, the USRG comes into the challenge as the only Asian team to compete with other teams comprised of students and researchers of American and European backgrounds where the culture of motorsports is more deep-rooted.
For CES 2022, Professor David Hyunchul Shim’s research team was able to successfully develop a software that controlled the racing car to comply with the race flags and regulations while going up to 240 km/h all on its on.
Photo 3. KAIST Team’s vehicle on Las Vegas Motor Speedway during the IAC @ CES 2022
In the IAC @ CES 2023, the official racing vehicle AV-23, is a converted version of IL-15, the official racing car for Indy 500, fully automated while maintaining the optimal design for high-speed racing, and was upgraded from the last year’s competition taking up the highest speed up to 300 km/h.
This year’s competition, will develop on last year’s head-to-head autonomous racing and take the form of the single elimination tournament to have the cars overtake the others without any restrictions on the driving course, which would have the team that constantly drives at the fastest speed will win the competition.
Photo 4. KAIST Team’s vehicle overtaking the Italian team, PoliMOVE’s vehicle during one of the race in the IAC @ CES 2022
Professor Shim's team further developed on the CES 2022 certified software to fine tune the external recognition mechanisms and is now focused on precise positioning and driving control technology that factors into maintaining stability even when driving at high speed.
Professor Shim's research team won the Autonomous Driving Competition hosted by Hyundai Motor Company in 2021. Starting with this CES 2023 competition, they signed a partnership contract with Hyundai to receive financial support to participate in the CES competition and share the latest developments and trends of autonomous driving technology with Hyundai Motor's research team.
During CES 2023, the research team will also participate in other events such as the exhibition by the KAIST racing team at the IAC’s official booth located in the West Hall.
Professor David Hyunchul Shim said, “With these competitions being held overseas, there were many difficulties having to keep coming back, but the students took part in it diligently, for which I am deeply grateful. Thanks to their efforts, we were able to continue in this competition, which will be a way to verify the autonomous driving technology that we developed ourselves over the past 13 years, and I highly appreciate that.”
“While high-speed autonomous driving technology is a technology that is not yet sought out in Korea, but it can be applied most effectively for long-distance travel in the Korea,” he went on to add. “It has huge advantages in that it does not require constructions for massive infrastructure that costs enormous amount of money such as high-speed rail or urban aviation and with our design, it is minimally affected by weather conditions.” he emphasized.
On a different note, the IAC @ CES 2023 is co-hosted by the Consumer Technology Association (CTA) and Energy Systems Network (ESN), the organizers of CES. Last year’s IAC winner, Technische Universität München of Germany, and MIT-PITT-RW, a team of Massachusetts Institute of Technology (Massachusetts), University of Pittsburgh (Pennsylvania), Rochester Institute of Technology (New York), University of Waterloo (Canada), with and the University of Waterloo, along with TII EuroRacing - University of Modena and Reggio Emilia (Italy), Technology Innovation Institute (United Arab Emirates), and five other teams are in the race for the win against KAIST.
Photo 5. KAIST Team’s vehicle on the track during the IAC @ CES 2022
The Indy Autonomous Challenge is scheduled to hold its fifth competition at the Monza track in Italy in June 2023 and the sixth competition at CES 2024.
2023.01.05 View 7318 -
A Quick but Clingy Creepy-Crawler that will MARVEL You
Engineered by KAIST Mechanics, a quadrupedal robot climbs steel walls and crawls across metal ceilings at the fastest speed that the world has ever seen.
< Photo 1. (From left) KAIST ME Prof. Hae-Won Park, Ph.D. Student Yong Um, Ph.D. Student Seungwoo Hong >
- Professor Hae-Won Park's team at the Department of Mechanical Engineering developed a quadrupedal robot that can move at a high speed on ferrous walls and ceilings.
- It is expected to make a wide variety of contributions as it is to be used to conduct inspections and repairs of large steel structures such as ships, bridges, and transmission towers, offering an alternative to dangerous or risky activities required in hazardous environments while maintaining productivity and efficiency through automation and unmanning of such operations.
- The study was published as the cover paper of the December issue of Science Robotics.
KAIST (President Kwang Hyung Lee) announced on the 26th that a research team led by Professor Hae-Won Park of the Department of Mechanical Engineering developed a quadrupedal walking robot that can move at high speed on steel walls and ceilings named M.A.R.V.E.L. - rightly so as it is a Magnetically Adhesive Robot for Versatile and Expeditious Locomotion as described in their paper, “Agile and Versatile Climbing on Ferromagnetic Surfaces with a Quadrupedal Robot.” (DOI: 10.1126/scirobotics.add1017)
To make this happen, Professor Park's research team developed a foot pad that can quickly turn the magnetic adhesive force on and off while retaining high adhesive force even on an uneven surface through the use of the Electro-Permanent Magnet (EPM), a device that can magnetize and demagnetize an electromagnet with little power, and the Magneto-Rheological Elastomer (MRE), an elastic material made by mixing a magnetic response factor, such as iron powder, with an elastic material, such as rubber, which they mounted on a small quadrupedal robot they made in-house, at their own laboratory. These walking robots are expected to be put into a wide variety of usage, including being programmed to perform inspections, repairs, and maintenance tasks on large structures made of steel, such as ships, bridges, transmission towers, large storage areas, and construction sites.
This study, in which Seungwoo Hong and Yong Um of the Department of Mechanical Engineering participated as co-first authors, was published as the cover paper in the December issue of Science Robotics.
< Image on the Cover of 2022 December issue of Science Robotics >
Existing wall-climbing robots use wheels or endless tracks, so their mobility is limited on surfaces with steps or irregularities. On the other hand, walking robots for climbing can expect improved mobility in obstacle terrain, but have disadvantages in that they have significantly slower moving speeds or cannot perform various movements.
In order to enable fast movement of the walking robot, the sole of the foot must have strong adhesion force and be able to control the adhesion to quickly switch from sticking to the surface or to be off of it. In addition, it is necessary to maintain the adhesion force even on a rough or uneven surface.
To solve this problem, the research team used the EPM and MRE for the first time in designing the soles of walking robots. An EPM is a magnet that can turn on and off the electromagnetic force with a short current pulse. Unlike general electromagnets, it has the advantage that it does not require energy to maintain the magnetic force. The research team proposed a new EPM with a rectangular structure arrangement, enabling faster switching while significantly lowering the voltage required for switching compared to existing electromagnets.
In addition, the research team was able to increase the frictional force without significantly reducing the magnetic force of the sole by covering the sole with an MRE. The proposed sole weighs only 169 g, but provides a vertical gripping force of about *535 Newtons (N) and a frictional force of 445 N, which is sufficient gripping force for a quadrupedal robot weighing 8 kg.
* 535 N converted to kg is 54.5 kg, and 445 N is 45.4 kg. In other words, even if an external force of up to 54.5 kg in the vertical direction and up to 45.4 kg in the horizontal direction is applied (or even if a corresponding weight is hung), the sole of the foot does not come off the steel plate.
MARVEL climbed up a vertical wall at high speed at a speed of 70 cm per second, and was able to walk while hanging upside down from the ceiling at a maximum speed of 50 cm per second. This is the world's fastest speed for a walking climbing robot. In addition, the research team demonstrated that the robot can climb at a speed of up to 35 cm even on a surface that is painted, dirty with dust and the rust-tainted surfaces of water tanks, proving the robot's performance in a real environment. It was experimentally demonstrated that the robot not only exhibited high speed, but also can switch from floor to wall and from wall to ceiling, and overcome 5-cm high obstacles protruding from walls without difficulty.
The new climbing quadrupedal robot is expected to be widely used for inspection, repair, and maintenance of large steel structures such as ships, bridges, transmission towers, oil pipelines, large storage areas, and construction sites. As the works required in these places involves risks such as falls, suffocation and other accidents that may result in serious injuries or casualties, the need for automation is of utmost urgency.
One of the first co-authors of the paper, a Ph.D. student, Yong Um of KAIST’s Department of Mechanical Engineering, said, "By the use of the magnetic soles made up of the EPM and MRE and the non-linear model predictive controller suitable for climbing, the robot can speedily move through a variety of ferromagnetic surfaces including walls and ceilings, not just level grounds. We believe this would become a cornerstone that will expand the mobility and the places of pedal-mobile robots can venture into." He added, “These robots can be put into good use in executing dangerous and difficult tasks on steel structures in places like the shipbuilding yards.”
This research was carried out with support from the National Research Foundation of Korea's Basic Research in Science & Engineering Program for Mid-Career Researchers and Korea Shipbuilding & Offshore Engineering Co., Ltd..
< Figure 1. The quadrupedal robot (MARVEL) walking over various ferrous surfaces. (A) vertical wall (B) ceiling. (C) over obstacles on a vertical wall (D) making floor-to-wall and wall-to-ceiling transitions (E) moving over a storage tank (F) walking on a wall with a 2-kg weight and over a ceiling with a 3-kg load. >
< Figure 2. Description of the magnetic foot (A) Components of the magnet sole: ankle, Square Eletro-Permanent Magnet(S-EPM), MRE footpad. (B) Components of the S-EPM and MRE footpad. (C) Working principle of the S-EPM. When the magnetization direction is aligned as shown in the left figure, magnetic flux comes out of the keeper and circulates through the steel plate, generating holding force (ON state). Conversely, if the magnetization direction is aligned as shown in the figure on the right, the magnetic flux circulates inside the S-EPM and the holding force disappears (OFF state). >
Video Introduction: Agile and versatile climbing on ferromagnetic surfaces with a quadrupedal robot - YouTube
2022.12.30 View 12711 -
“3D sketch” Your Ideas and Bring Them to Life, Instantly!
Professor Seok-Hyung Bae’s research team at the Department of Industrial Design developed a novel 3D sketching system that rapidly creates animated 3D concepts through simple user interactions like sketching on a piece of paper or playing a toy.
Foldable drones, transforming vehicles, and multi-legged robots from sci-fi movies are now becoming commonplace thanks to technological progress. However, designing them remains a difficult challenge even for skilled experts, because complex design decisions must be made regarding not only their form, but also the structure, poses, and motions, which are interdependent on one another.
Creating a 3D concept comprising of multiple moving parts connected by different types of joints using a traditional 3D CAD tool, which is more suited for processing precise and elaborate modeling, is a painstaking and time-consuming process. This presents a major bottleneck for the workflow during the early stage of design, in which it is preferred that as many ideas are tried and discarded out as quickly as possible in order to explore a wide range of possibilities in the shortest amount of time.
A research team led by Professor Bae has focused on designers’ freehand sketches drew up with a pen on a paper that serve as the starting point for virtually all design projects. This led them to develop their 3D sketching technology to generate desired 3D curves from the rough but expressive 2D strokes drawn with a digital stylus on a digital tablet.
Their latest research helps designers bring their 3D sketches to life almost instantly. Using the intuitive set of multi-touch gestures the team successfully designed and implemented, designers can handle the 3D sketches they are working on with their fingers as if they are playing with toys and put them into animation in no time.
< Figure 1. A novel 3D sketching system for rapidly designing articulated 3D concepts with a small set of coherent pen and multi-touch gestures. (a) Sketching: A 3D sketch curve is created by marking a pen stroke that is projected onto a sketch plane widget. (b) Segmenting: Entire or partial sketch curves are added to separate parts that serve as links in the kinematic chain. (c) Rigging: Repeatedly demonstrating the desired motion of a part leaves behind a trail, from which the system infers a joint. (d) Posing: Desired poses can be achieved through actuating joints via forward or inverse kinematics. (e) Filming: A sequence of keyframes specifying desired poses and viewpoints is connected as a smooth motion. >
< Figure 2. (a) Concept drawing of an autonomous excavator. It features (b, c) four caterpillars that swivel for high maneuverability, (d) an extendable boom and a bucket connected by multiple links, and (e) a rotating platform. The concept’s designer, who had 8 years of work experience, estimated that it would take 1-2 weeks to express and communicate such a complex articulated object with existing tools. With the proposed system, it took only 2 hours and 52 minutes. >
The major findings of their work were published under the title “Rapid Design of Articulated Objects” in ACM Transactions on Graphics (impact factor: 7.403), the top international journal in the field of computer graphics, and presented at ACM SIGGRAPH 2022 (h5-index: 103), the world’s largest international academic conference in the field, which was held back in August in Vancouver, Canada with Joon Hyub Lee, a Ph.D. student of the Department of Industrial Design as the first author.
The ACM SIGGRAPH 2022 conference was reportedly attended by over 10,000 participants including researchers, artists, and developers from world-renowned universities; film, animation, and game studies, such as Marvel, Pixar, and Blizzard; high-tech manufacturers, such as Lockheed Martin and Boston Dynamics; and metaverse platform companies, such as Meta and Roblox.
< Figure 3. The findings of Professor Bae’s research team were published in ACM Transactions on Graphics, the top international academic journal in the field of computer graphics, and presented at ACM SIGGRAPH 2022, the largest international academic conference held in conjunction early August in Vancouver, Canada. The team’s live demo at the Emerging Technologies program was highly praised by numerous academics and industry officials and received an Honorable Mention. >
The team was also invited to present their technical paper as a demo and a special talk at the Emerging Technologies program at ACM SIGGRAPH 2022 as one of the top-three impactful technologies. The live performance, in which Hanbit Kim, a Ph.D. student of the Department of Industrial Design at KAIST and a co-author, sketched and animated a sophisticated animal-shaped robot from scratch in a matter of a few minutes, wowed the audience and won the Honorable Mention Award from the jury.
Edwin Catmull, the co-founder of Pixar and a keynote speaker at the SIGGRAPH conference, praised the team’s research on 3D sketching as “really excellent work” and “a kind of tool that would be useful to Pixar's creative model designers.”
This technology, which became virally popular in Japan after featuring in an online IT media outlet and attracting more than 600K views, received a special award from the Digital Content Association of Japan (DCAJ) and was invited and exhibited for three days at Tokyo in November, as a part of Inter BEE 2022, the largest broadcasting and media expo in Japan.
“The more we come to understand how designers think and work, the more effective design tools can be built around that understanding,” said Professor Bae, explaining that “the key is to integrate different algorithms into a harmonious system as intuitive interactions.” He added that “this work wouldn’t have been possible if it weren’t for the convergent research environment cultivated by the Department of Industrial Design at KAIST, in which all students see themselves not only as aspiring creative designers, but also as practical engineers.”
By enabling designers to produce highly expressive animated 3D concepts far more quickly and easily in comparison to using existing methods, this new tool is expected to revolutionize design practices and processes in the content creation, manufacturing, and metaverse-related industries.
This research was funded by the Ministry of Science and ICT, and the National Research Foundation of Korea.
More info: https://sketch.kaist.ac.kr/publications/2022_siggraph_rapid_design
Video: https://www.youtube.com/watch?v=rsBl0QvSDqI
< Figure 4. From left to right: Ph.D. students Hanbit Kim, and Joon Hyub Lee and Professor Bae of the Department of Industrial Design, KAIST >
2022.11.23 View 6879 -
KAIST Team Develops Surface-Lighting MicroLED Patch with Significant Melanogenesis Inhibition Effect
A KAIST research team led by Ph.d candidate Jae Hee Lee and Professor Keon Jae Lee from the Department of Materials Science and Engineering has developed a surface-lighting microLED patch for UV-induced melanogenesis inhibition.
Melanin is brown or dark pigments existing in the skin, which can be abnormally synthesized by external UV or stress. Since the excessive melanin leads to skin diseases such as spots and freckles, proper treatment is required to return normal skin condition.
Recently, LED-based photo-stimulators have been released for skin care, however, their therapeutic effect is still controversial. Since conventional LED stimulators cannot conformally attach to the human skin, distance-induced side effects are caused by light loss and high heat transfer. To achieve effective phototreatment, the LED stimulator needs to be irradiated in contact with the human skin surface, enabling proper and uniform light deliver to the dermis with minimal optical loss.
In this work, the research team fabricated skin-attachable surface-lighting microLED (SµLED, 4 × 4 cm2) patch by utilizing a thousand of microLED chips and silica-embedded light diffusion layer. 100 µm-sized LED chips are vertically-interconnected for high flexibility and low heat generation, allowing its long-term operation on the human skin.
< Image 1. The overall concept of SµLED patch. a) SµLED patch operated on the human skin. b) Schematic illustration of SµLED patch structure. c) 4 × 4 cm2-sized SµLED patch. d) Schematic illustration of the advantages of SµLED patch such as efficient light delivery, low heat generation, and surface-lighting irradiation. >
The research team confirmed melanogenesis inhibition by irradiating the SµLED patch and the conventional LED (CLED) on the artificial human skin and mice dorsal skin. The SµLED-treated groups of human cells and mouse tissues showed minimal epidermal photo-toxicity and consistently effective reduction in synthesized melanin, compared to CLED-treated groups. In addition, significant suppression of proteins/catalysts expression involved in melanin synthesis such as MITF (microphthalmia-associated transcription factor), Melan-A and tyrosinase was verified.
< Image 2. The efficacy of melanogenesis inhibition on 3D human skin cells. a). Different irradiation conditions for a-MSH (major factor to stimulate melanin synthesis) treated cells. b) The ratio of pigmented area to total epidermis area. c) Relative variance of melanin level in 1 cm2-sized skin cells. A low variance means that melanin is evenly distributed, and a high variance means that the melanin is irregularly distributed. d) Optical images after in vitro experiments for 12 days. Scale bar, 1cm. e) Histological analysis of 3D skin, showing the greatest reduction in melanin after SµLED irradiation. Scale bar, 20 µm. >
< Image 3. The efficacy of melanogenesis inhibition on mouse dorsal skin. a) Optical images of mice dorsal skin after photo-treatment for 20 days. b) Histological analysis of mice dorsal skin. Less brown color means less expression of protein/catalysis involved in melanin synthesis. Scale bar, 50 µm. >
Prof. Keon Jae Lee said, “Our inorganic-based SµLED patch has outstanding characteristics in light efficiency, reliability, and durability. The SµLED patch is expected to give a great impact on the cosmetic field by reducing side effects and maximizing phototherapeutic effects.” The core technology of cosmetic SµLED has been transferred to Fronics co., Ltd, founded by Prof. Lee. Fronics is building foundry and equipment for mass production of SµLED masks for whole face cover and plans to release the products in March next year.
This paper entitled “Wearable Surface-Lighting Micro-Light-Emitting Diode Patch for Melanogenesis Inhibition” was published in the November 2022 issue of Advanced Healthcare Materials.
2022.11.22 View 7981 -
EE Professor Youjip Won Elected as the President of Korean Institute of Information Scientists and Engineers for 2024
< Professor Youjip Won of KAIST School of Electrical Engineering >
Professor Youjip Won of KAIST School of Electrical Engineering was elected as the President of Korean Institute of Information Scientists and Engineers (KIISE) for the Succeding Term for 2023 on November 4th, 2022. Professor Won will serve as the 39th President of KIISE for one year starting from Jan. 1, 2024. He is one of the leading experts on Operating Systems, with a particular emphasis on storage systems.
Korean Institute of Information Scientists and Engineers (KIISE), one of the most prestigious Korean academic institutions in the field of computer and software, was founded in 1973 and boasts a membership of over 42,000 people and 437 special/group members. KIISE is responsible for annually publishing 72 periodicals and holding 50 academic conferences.
2022.11.15 View 4143 -
Professor Shinhyun Choi’s team, selected for Nature Communications Editors’ highlight
[ From left, Ph.D. candidates See-On Park and Hakcheon Jeong, along with Master's student Jong-Yong Park and Professor Shinhyun Choi ]
See-On Park, Hakcheon Jeong, Jong-Yong Park - a team of researchers under the leadership of Professor Shinhyun Choi of the School of Electrical Engineering, developed a highly reliable variable resistor (memristor) array that simulates the behavior of neurons using a metal oxide layer with an oxygen concentration gradient, and published their work in Nature Communications. The study was selected as the Nature Communications' Editor's highlight, and as the featured article posted on the main page of the journal's website.
Link : https://www.nature.com/ncomms/
[ Figure 1. The featured image on the main page of the Nature Communications' website introducing the research by Professor Choi's team on the memristor for artificial neurons ]
Thesis title: Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing.
( https://doi.org/10.1038/s41467-022-30539-6 )
At KAIST, their research was introduced on the 2022 Fall issue of Breakthroughs, the biannual newsletter published by KAIST College of Engineering.
This research was conducted with the support from the Samsung Research Funding & Incubation Center of Samsung Electronics.
2022.11.01 View 5813 -
A New Family of Ducks joins the Feathery KAISTians
In October of this year, KAIST signed an 'Agreement for the Training Program for AI Semiconductor Designers' with Samsung Electronics, to conduct joint research and actively nurture master's and doctorate researchers in the field of Semiconductors designed exclusively for AI devices. To celebrate this commemorative agreement for cooperation bound for mutual success, Samsung Electronics gifted a set of 5 ducks to KAIST.
The Duck Pond and the Geese have been representing KAIST as famous mascots.
It all started back in 2000, when the incumbent President, Professor Kwang Hyung Lee served was then a professor at the Department of Bio and Brain Engineering, he first picked up a pack of ducks from Yuseong Market and started taking care of it on campus around the Carillon pond. While the ducks came and went, eventually being replaced with a pack of geese over the time, for more than 20 years, the pack of feathery KAISTians stole the eyes of the passersby and were loved by both the on-campus members and the visitors, alike.
The representative of the Samsung Electronics said that the pack of ducks comprising of a new breed contains the message of SEC that it hopes that the PIM semiconductor technology will grow to become the super-gap technology that would turn heads and grab attention of the world as the mascot of Korea's technological prowess under the combined care of KAIST and SEC.
Would the ducks find KAIST likable? We will keep you informed of how they are doing!
2022.11.01 View 3803