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KAIST Professor Jee-Hwan Ryu Receives Global IEEE Robotics Journal Best Paper Award
- Professor Jee-Hwan Ryu of Civil and Environmental Engineering receives the Best Paper Award from the Institute of Electrical and Electronics Engineers (IEEE) Robotics Journal, officially presented at ICRA, a world-renowned robotics conference.
- This is the highest level of international recognition, awarded to only the top 5 papers out of approximately 1,500 published in 2024.
- Securing a new working channel technology for soft growing robots expands the practicality and application possibilities in the field of soft robotics.
< Professor Jee-Hwan Ryu (left), Nam Gyun Kim, Ph.D. Candidate (right) from the KAIST Department of Civil and Environmental Engineering and KAIST Robotics Program >
KAIST (President Kwang-Hyung Lee) announced on the 6th that Professor Jee-Hwan Ryu from the Department of Civil and Environmental Engineering received the 2024 Best Paper Award from the Robotics and Automation Letters (RA-L), a premier journal under the IEEE, at the '2025 IEEE International Conference on Robotics and Automation (ICRA)' held in Atlanta, USA, on May 22nd.
This Best Paper Award is a prestigious honor presented to only the top 5 papers out of approximately 1,500 published in 2024, boasting high international competition and authority.
The award-winning paper by Professor Ryu proposes a novel working channel securing mechanism that significantly expands the practicality and application possibilities of 'Soft Growing Robots,' which are based on soft materials that move or perform tasks through a growing motion similar to plant roots.
< IEEE Robotics Journal Award Ceremony >
Existing soft growing robots move by inflating or contracting their bodies through increasing or decreasing internal pressure, which can lead to blockages in their internal passages. In contrast, the newly developed soft growing robot achieves a growing function while maintaining the internal passage pressure equal to the external atmospheric pressure, thereby successfully securing an internal passage while retaining the robot's flexible and soft characteristics.
This structure allows various materials or tools to be freely delivered through the internal passage (working channel) within the robot and offers the advantage of performing multi-purpose tasks by flexibly replacing equipment according to the working environment.
The research team fabricated a prototype to prove the effectiveness of this technology and verified its performance through various experiments. Specifically, in the slide plate experiment, they confirmed whether materials or equipment could pass through the robot's internal channel without obstruction, and in the pipe pulling experiment, they verified if a long pipe-shaped tool could be pulled through the internal channel.
< Figure 1. Overall hardware structure of the proposed soft growing robot (left) and a cross-sectional view composing the inflatable structure (right) >
Experimental results demonstrated that the internal channel remained stable even while the robot was growing, serving as a key basis for supporting the technology's practicality and scalability.
Professor Jee-Hwan Ryu stated, "This award is very meaningful as it signifies the global recognition of Korea's robotics technology and academic achievements. Especially, it holds great significance in achieving technical progress that can greatly expand the practicality and application fields of soft growing robots. This achievement was possible thanks to the dedication and collaboration of the research team, and I will continue to contribute to the development of robotics technology through innovative research."
< Figure 2. Material supplying mechanism of the Soft Growing Robot >
This research was co-authored by Dongoh Seo, Ph.D. Candidate in Civil and Environmental Engineering, and Nam Gyun Kim, Ph.D. Candidate in Robotics. It was published in IEEE Robotics and Automation Letters on September 1, 2024.
(Paper Title: Inflatable-Structure-Based Working-Channel Securing Mechanism for Soft Growing Robots, DOI: 10.1109/LRA.2024.3426322)
This project was supported simultaneously by the National Research Foundation of Korea's Future Promising Convergence Technology Pioneer Research Project and Mid-career Researcher Project.
2025.06.09 View 6671 -
RAIBO Runs over Walls with Feline Agility... Ready for Effortless Search over Mountaineous and Rough Terrains
< Photo 1. Research Team Photo (Professor Jemin Hwangbo, second from right in the front row) >
KAIST's quadrupedal robot, RAIBO, can now move at high speed across discontinuous and complex terrains such as stairs, gaps, walls, and debris. It has demonstrated its ability to run on vertical walls, leap over 1.3-meter-wide gaps, sprint at approximately 14.4 km/h over stepping stones, and move quickly and nimbly on terrain combining 30° slopes, stairs, and stepping stones. RAIBO is expected to be deployed soon for practical missions such as disaster site exploration and mountain searches.
Professor Jemin Hwangbo's research team in the Department of Mechanical Engineering at our university announced on June 3rd that they have developed a quadrupedal robot navigation framework capable of high-speed locomotion at 14.4 km/h (4m/s) even on discontinuous and complex terrains such as walls, stairs, and stepping stones.
The research team developed a quadrupedal navigation system that enables the robot to reach its target destination quickly and safely in complex and discontinuous terrain.
To achieve this, they approached the problem by breaking it down into two stages: first, developing a planner for planning foothold positions, and second, developing a tracker to accurately follow the planned foothold positions.
First, the planner module quickly searches for physically feasible foothold positions using a sampling-based optimization method with neural network-based heuristics and verifies the optimal path through simulation rollouts.
While existing methods considered various factors such as contact timing and robot posture in addition to foothold positions, this research significantly reduced computational complexity by setting only foothold positions as the search space. Furthermore, inspired by the walking method of cats, the introduction of a structure where the hind feet step on the same spots as the front feet further significantly reduced computational complexity.
< Figure 1. High-speed navigation across various discontinuous terrains >
Second, the tracker module is trained to accurately step on planned positions, and tracking training is conducted through a generative model that competes in environments of appropriate difficulty.
The tracker is trained through reinforcement learning to accurately step on planned plots, and during this process, a generative model called the 'map generator' provides the target distribution.
This generative model is trained simultaneously and adversarially with the tracker to allow the tracker to progressively adapt to more challenging difficulties. Subsequently, a sampling-based planner was designed to generate feasible foothold plans that can reflect the characteristics and performance of the trained tracker.
This hierarchical structure showed superior performance in both planning speed and stability compared to existing techniques, and experiments proved its high-speed locomotion capabilities across various obstacles and discontinuous terrains, as well as its general applicability to unseen terrains.
Professor Jemin Hwangbo stated, "We approached the problem of high-speed navigation in discontinuous terrain, which previously required a significantly large amount of computation, from the simple perspective of how to select the footprint positions. Inspired by the placements of cat's paw, allowing the hind feet to step where the front feet stepped drastically reduced computation. We expect this to significantly expand the range of discontinuous terrain that walking robots can overcome and enable them to traverse it at high speeds, contributing to the robot's ability to perform practical missions such as disaster site exploration and mountain searches."
This research achievement was published in the May 2025 issue of the international journal Science Robotics.
Paper Title: High-speed control and navigation for quadrupedal robots on complex and discrete terrain, (https://www.science.org/doi/10.1126/scirobotics.ads6192)YouTube Link: https://youtu.be/EZbM594T3c4?si=kfxLF2XnVUvYVIyk
2025.06.04 View 8123 -
Professor Hyun Myung's Team Wins First Place in a Challenge at ICRA by IEEE
< Photo 1. (From left) Daebeom Kim (Team Leader, Ph.D. student), Seungjae Lee (Ph.D. student), Seoyeon Jang (Ph.D. student), Jei Kong (Master's student), Professor Hyun Myung >
A team of the Urban Robotics Lab, led by Professor Hyun Myung from the KAIST School of Electrical Engineering, achieved a remarkable first-place overall victory in the Nothing Stands Still Challenge (NSS Challenge) 2025, held at the 2025 IEEE International Conference on Robotics and Automation (ICRA), the world's most prestigious robotics conference, from May 19 to 23 in Atlanta, USA.
The NSS Challenge was co-hosted by HILTI, a global construction company based in Liechtenstein, and Stanford University's Gradient Spaces Group. It is an expanded version of the HILTI SLAM (Simultaneous Localization and Mapping)* Challenge, which has been held since 2021, and is considered one of the most prominent challenges at 2025 IEEE ICRA.*SLAM: Refers to Simultaneous Localization and Mapping, a technology where robots, drones, autonomous vehicles, etc., determine their own position and simultaneously create a map of their surroundings.
< Photo 2. A scene from the oral presentation on the winning team's technology (Speakers: Seungjae Lee and Seoyeon Jang, Ph.D. candidates of KAIST School of Electrical Engineering) >
This challenge primarily evaluates how accurately and robustly LiDAR scan data, collected at various times, can be registered in situations with frequent structural changes, such as construction and industrial environments. In particular, it is regarded as a highly technical competition because it deals with multi-session localization and mapping (Multi-session SLAM) technology that responds to structural changes occurring over multiple timeframes, rather than just single-point registration accuracy.
The Urban Robotics Lab team secured first place overall, surpassing National Taiwan University (3rd place) and Northwestern Polytechnical University of China (2nd place) by a significant margin, with their unique localization and mapping technology that solves the problem of registering LiDAR data collected across multiple times and spaces. The winning team will be awarded a prize of $4,000.
< Figure 1. Example of Multiway-Registration for Registering Multiple Scans >
The Urban Robotics Lab team independently developed a multiway-registration framework that can robustly register multiple scans even without prior connection information. This framework consists of an algorithm for summarizing feature points within scans and finding correspondences (CubicFeat), an algorithm for performing global registration based on the found correspondences (Quatro), and an algorithm for refining results based on change detection (Chamelion). This combination of technologies ensures stable registration performance based on fixed structures, even in highly dynamic industrial environments.
< Figure 2. Example of Change Detection Using the Chamelion Algorithm>
LiDAR scan registration technology is a core component of SLAM (Simultaneous Localization And Mapping) in various autonomous systems such as autonomous vehicles, autonomous robots, autonomous walking systems, and autonomous flying vehicles.
Professor Hyun Myung of the School of Electrical Engineering stated, "This award-winning technology is evaluated as a case that simultaneously proves both academic value and industrial applicability by maximizing the performance of precisely estimating the relative positions between different scans even in complex environments. I am grateful to the students who challenged themselves and never gave up, even when many teams abandoned due to the high difficulty."
< Figure 3. Competition Result Board, Lower RMSE (Root Mean Squared Error) Indicates Higher Score (Unit: meters)>
The Urban Robotics Lab team first participated in the SLAM Challenge in 2022, winning second place among academic teams, and in 2023, they secured first place overall in the LiDAR category and first place among academic teams in the vision category.
2025.05.30 View 8797 -
KAIST Wins CES 2025 Innovation Award, Showcasing Innovative Technologies
KAIST will showcase innovative technologies at the world’s largest technology fair, the Consumer Electronics Show (CES 2025). In addition, KAIST startups VIRNECT Inc., Standard Energy Inc., A2US Inc., and Panmnesia, Inc. won the 2025 CES Innovation Awards.
< Image 1. 3D-Graphical Profile of CES 2025 KAIST Exhibition Booth >
KAIST (President Kwang-Hyung Lee) announced on the 31st that it will operate a 140㎡ standalone booth at CES Eureka Park, which will be held in Las Vegas, USA from January 7th to 10th next year, to showcase KAIST's innovative technologies to global companies and investors.
KAIST startups VIRNECT, Standard Energy, A2US, and Panmnesia, Inc. won the 2025 CES Innovation Awards. ▴VIRNECT won the Innovation Award in the ‘Industrial Equipment and Machinery’ category for ‘VisionX’, an AI-based smart glass for industrial sites; ▴Standard Energy Co., Ltd. won the Innovation Award in the ‘Smart City’ category for developing the world’s first vanadium-ion battery; ▴A2US won the Innovation Award in the ‘Environment & Energy’ category for its portable air purifier that eliminates bacteria, odors, and fine dust in the air with just water droplets; ▴Panmnesia, Inc. won the Innovation Award in the ‘Computer Peripherals and Accessories’ category for its ‘CXL-based GPU Memory Expansion Kit’ that can drastically reduce the cost of building AI infrastructure.
< Image 2. (From left on the top row) VIRNECT, Standard Energy, (From left on the bottom row) A2US, Panmnesia, Inc. >
This exhibition will feature 15 startups that are standing out in cutting-edge technologies such as artificial intelligence (AI), robotics, mobility, and sustainability. In particular, AI-based deep tech startups in various industries such as logistics, architecture, and medicine will take up half of the total, showcasing the companies’ innovative AI technologies.
Polyphenol Factory Co.,Ltd introduces ‘Grabity’, a hair loss shampoo launched domestically, which applies the patented ingredient ‘LiftMax 308™’ that forms an instantaneous protective layer on the hair during the shampooing process. A real-time demonstration will be held at this exhibition hall so that visitors can experience the effects of the ingredient directly, and plans to enter the global market starting with the launch on Amazon in the US in January 2025.
VIRNECT will present ‘VisionX’, a prototype that won the Innovation Award this time. The product provides a chatbot AI through an AI voice interface, and has a function that allows users to check the status of the equipment in real time through conversations with the AI and receive troubleshooting guidance through voice conversations, so users can experience it directly at the KAIST Hall.
‘Standard Energy’ plans to exhibit ‘Energy Tile’, an indoor ESS that utilizes the world’s first vanadium ion battery (hereinafter referred to as VIB). VIB is absolutely safe from fire and has high installation flexibility, so it can be applied to smart cities and AI data centers.
‘A2US’ is the only company in the world that has hydroxyl radical water production technology, and won the Innovation Award for its first product, an air purifier. In the future, it is expected to be widely commercialized in air and water purification, smart farms, food tech, and semiconductor cleaning using safe and environmentally friendly hydroxyl radical water.
Panmnesia, Inc. won the CES Innovation Award for its GPU memory expansion solution equipped with its CXL 3.1 IP. By connecting a memory expansion device using Panmnesia’s CXL IP, the GPU’s memory capacity can be expanded to the terabyte level. Following the Innovation Award for ‘CXL-equipped AI Accelerator’ at CES 2024 last year, it is the only company to have won the Innovation Award for its AI-oriented CXL solution for two consecutive years.
In addition, technologies from a total of 15 companies will be introduced, including ▴Omelet ▴NEXTWAVE ▴Planby Technologies ▴Cosmo Bee ▴ImpactAI ▴Roen Surgical ▴DIDEN Roboticss ▴Autopedia ▴OAQ ▴HydroXpand ▴BOOKEND ▴Sterri.
On the central stage of the KAIST Hall, KAIST students selected as CES Student Supporters will conduct interviews with participating companies and promote the companies' innovative technologies and solutions. On the 8th, from 5 PM to 7 PM, a KAIST NIGHT event will be held where pre-invited investors and participating companies can network.
Keon Jae Lee, the head of the Institute of Technology Value Creation, said, “Through CES 2025, we will showcase innovative technologies and solutions from startups based on KAIST’s deep science and deep tech, and lead commercialization in cutting-edge technology fields such as AI, robotics, mobility, and environment/energy. KAIST plans to further promote technology commercialization by supporting the growth and marketing of innovative startups through the Institute of Technology Value Creation and by strengthening global networks and expanding cooperation opportunities.”
2024.12.31 View 12061 -
KAIST’s RAIBO2 becomes the World’s First Robo-dog to Successfully Complete a Full-course Marathon
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.
2024.11.17 View 13151 -
KAIST’s Beach-Roaming Quadrupedal Robot “RAIBO” to Run a Marathon!
“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 >
2024.11.15 View 9385 -
Team KAIST Crowned Champion for their World’s Best Ironman, Winning their 2nd Consecutive Win at the Cyborg Olympics
< 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
2024.10.28 View 13577 -
KAIST Introduces a Wearable Robot that Walks and Puts itself on to Disabled Persons
< Photo 1. WalkON Suit F1 - walking demonstration >
KAIST researchers have unveiled a new wearable robot developed for completely paralyzed persons that can walk to them so that the user can wear it right out of their wheelchairs without the help from others. Also, it was announced that Professor Kyoungchul Kong's team from KAIST will be participating in the wearable robot category of the 3rd Cybathlon, which is being held four years after the team’s gold medal win in 2020.
KAIST (President Kwang-Hyung Lee) announced this new version of the wearable robot for paraplegic people, WalkON Suit F1, by Professor Kyoungchul Kong (CEO and founder of Angel Robotics) of KAIST Department of Mechanical Engineering on the 24th of October.
< Photo 2. (From left) Professor Kyoungchul Kong of the Department of Mechanical Engineering, Researcher Seunghwan Kim (the competing athlete), and PhD candidate Jeongsu Park (the leader of Team KAIST) >
WalkON Suit is a wearable robot for people suffering with paraplegic disabilities that the research team has been continuously researching since 2015. This robot targets to assist persons with American Spinal Injury Association (ASIA) Impairment Scale – A (complete paralysis) grade injury, the most severe level of paraplegia. Therefore, its development purpose is different from that of other rehabilitation therapy and muscle strength assisting robots currently being supplied nationally by Angel Robotics.
Professor Kong's research team first announced WalkON Suit 1 in 2016, and then introduced WalkON Suit 4 in 2020, increasing the walking speed to 3.2 km/h, achieving the normal walking speed of people with no disabilities. In addition, it demonstrated the ability to pass through obstacles such as narrow passages, doors, and stairs that can be encountered in daily life.
However, it had the same fundamental problem all wearable robots have, which is that they require the help of others to wear the robot. While you can walk without help from others once you are wearing the robot, you needed someone's help to put it on to begin with.
The newly released WalkON Suit F1 presented a technical solution to this fundamental problem. It applied a frontal-docking method instead of a rear-sitting method so that you can wear the robot right away without getting out of the wheelchair and into the robot, which would require help from others mid-transition.
< Photo 3. WalkON Suit F1 - suiting-up demonstration >
In addition, before wearing the robot, it can walk on its own like a humanoid robot and approaches the user. It is also implemented a function that actively controls the center of its weight against the pull of gravity so that it maintains balance without falling over even if the user pushes the robot otherwise. The outer design of the WalkON Suit F1, which crosses between a humanoid and a wearable robot, was done by Professor Hyunjoon Park of the Department of Industrial Design at KAIST.
The original function of the wearable robot has also been greatly improved. The performance of the balance control was improved to allow the free use of both hands in upright state, as well as the freedom to take several steps without a cane.
Technological advancements at the components level are also noteworthy. Through close collaboration with Angel Robotics, all core components of the robot, such as the motor, reducer, motor driver, and main circuit, have been domestically produced. The output density of the motor and reducer modules has been improved by about two folds (based on power per weight) compared to the research team's existing technology, and the control performance of the motor driver has been improved by about three times (based on frequency response speed) compared to the best overseas technology.
In particular, the embedded software technology of the motor driver has been significantly improved so that advanced motion control algorithms can be stably implemented without using expensive higher-level controllers. In addition, visual recognition system for obstacle detection and an AI board for neural network application have been installed.
< Figure 1. WalkON Suit F1 shape and main specifications >
Professor Kong explained, “WalkON Suit is the culmination of wearable robot technology for the disabled,” and added, “The numerous components, control, and module technologies derived from WalkON Suit are setting the standard for the entire wearable robot industry.”
Professor Kong’s research team revealed WalkON Suit F1 and announced that they will be participating in the 3rd Cybathlon, which is being held after four years since the last event. In this competition, which will be held on October 27, Professor Kong’s lab, the Exo Lab will be participating with Jeongsu Park, a Ph.D. Student, as the leader and Seunghwan Kim, the lab’s staff researcher with complete paralysis, as the competing athlete.
The difficulty of the missions in this competition has been significantly increased compared to the previous competition, and the number of missions has increased from six to ten. Some missions have been criticized for being overly challenging, going beyond the level that can be encountered in everyday life.
< Photo 4. Cybathlon stadium (Angel Robotics Asia Hub) >
Regarding this, the team leader Jeongsu Park expressed his ambition, saying, “Since we already won first place in the previous competition, our goal in this competition is to show the technological gap rather than competing for rankings.”
The Cybathlon is a cyborg Olympics held every four years in Switzerland. This competition will be held in a hybrid format, with some participants taking part in Switzerland while others broadcasting live from stadiums in their own country on October 27. Professor Kong's research team will be participating via live broadcast from the competition facilities installed in Angel Robotics' Advanced Research Institute (Planet Daejeon).
< Photo 5. Photo of Team KAIST participating in Cybathlon 2024 >
The demonstration video of WalkON Suit F1 can be viewed through the link below.
Link: https://www.youtube.com/@KyoungchulKong_EXO-Lab
2024.10.24 View 19247 -
The 3rd Global Entrepreneurship Summer School (GESS 2024) Successfully Completed in Silicon Valley
The 2024 Global Entrepreneurship Summer School (2024 KAIST GESS), hosted by the Office of Global Initiatives under the KAIST International Office (Director Man-Sung Yim), was held for the third time. This program allows students to visit Silicon Valley, a global startup hub, to directly experience its famous startup ecosystem and develop their capabilities for global expansion. A total of 20 students were selected through applications, interviews, final presentations, mentoring, and peer evaluations. Additionally, 17 students from the KAIST Impact MBA course at the KAIST Business School also participated.
Before starting the Silicon Valley program, participants received mentoring on business model development and pitching advice from a senior entrepreneur at KAIST for about two months, beginning last May. Afterward, they developed business items for each team at KAIST’s main campus in Daejeon. For seven days, starting from June 23rd, workshops were held under the themes of global entrepreneurship, learning through failure, capital and network, and startup culture at KOTRA Silicon Valley Trade Center, JP Morgan, and Plug and Play Tech Center. This program's lecture series provided prospective entrepreneurs with the opportunity to systematically learn the mindset and gain the experience needed to start a global business.
The participants also visited local companies and gained experience in the field of global technology startups. Visits included Bear Robotics (CEO John Ha), Soundable Health (CEO Cathering Song), ImpriMed (CEO Sungwon Lim), Phantom AI (CEO Hyunggi Cho), B Garage (CEO Aiden Kim), and Simple Steps (CEO Doyeon Kim). Lectures contained vivid experiences from Silicon Valley CEOs and company tours boosted the students' passion for entrepreneurship. In particular, Doyeon Kim, CEO of Simple Steps, which helps prevent career breaks for Korean female immigrants in Silicon Valley and allows talented female immigrants to demonstrate their abilities in society, said, “As a KAIST alumna entrepreneur, it was meaningful to share my experience with this generation of students who dream of starting a global business and creating social enterprises in the United States.”
This program also included a tour of Silicon Valley's big tech companies that have made a significant impact on the digital ecosystem through technological advancement and innovation. This included Broadcom, which maintains a strong global presence in the semiconductor and infrastructure software technology fields. At the invitation of Chairman Hock Tan, GESS participants had the opportunity to attend his lecture and ask questions. Chairman Tan, who received an honorary doctorate in engineering from KAIST last February, emphasized that experiencing failure and giving consistent effort over a long period of time are more important than anything else in order to grow as a global entrepreneur, and that technologies influencing the global market evolve over generations.
< Photo. Group photo of GESS 2024 participants at Broadcom with Chairman Hock Tan (center) ⓒBroadcom>
As part of this program, participants conducted a volunteer program called 'Let's play with AI+ Tech' with the Sunnyvale community in Silicon Valley and Foothill College to help grow together with the community. Through this program, GESS participants cultivated the virtues of a global leader. In this volunteer activity, low-income elementary school students and parents from the Sunnyvale community participated in chatbot training led by KAIST students, providing an opportunity to work with underprivileged groups in the local community.
In the final pitching event, the highlight of the program, local venture investors from Silicon Valley were invited as judges and evaluated the pitches for each team's business items. The participating students, who developed their own business models while receiving advice through face-to-face mentoring from a professional accelerator in Silicon Valley, showcased their creative and innovative ideas, presenting themselves as future global entrepreneurs. Merey Makhmutova (BS in Civil and Environmental Engineering) from the K-Bridge team, who won the final pitch, expressed her ambition: “Even before GESS pitch day, our team kept refining the pitch deck as we attended the lectures and benefitted from the mentoring. Our intense teamwork was a significant reason why we ultimately won first prize.” She added that K-Bridge aims to win an award at the upcoming UKC Pitching Competition and expressed her gratitude for being able to participate in this program. Arseniy Kan (BS in Electrical Engineering) from the KAIST Enablers team, who took second place, said, “The 2024 KAIST GESS Program became the most unforgettable and precious opportunity of my lifetime, and I dream of using this opportunity as a stepping stone to becoming a global entrepreneur.“ Additionally, Kangster (CEO Kang Kim), who won the Impact MBA final pitching session, had the opportunity to secure a meeting with a local investment company after their GESS final pitch.
The 2024 KAIST GESS was held in cooperation with the KAIST International Office, the KAIST College of Business, and Startup KAIST. Director Man-Sung Yim from the Office of Global Initiatives, who hosted the event, said, “KAIST students will grow into leaders with global influence and contribute to the international community by creating global value. At the same time, we hope to raise the international status of our university.” Professor Sangchan Park, who led the 17 Impact MBA students in this educational program, added, “Meeting with companies leading the global market and visiting Silicon Valley has been a valuable learning experience for students aiming to start a global startup.”
KAIST plans to continue promoting its global entrepreneurship education program by enriching its curriculum each year and helping students grow into entrepreneurs with the virtues of global leaders.
2024.07.03 View 14825 -
Team KAIST placed among top two at MBZIRC Maritime Grand Challenge
Representing Korean Robotics at Sea: KAIST’s 26-month strife rewarded
Team KAIST placed among top two at MBZIRC Maritime Grand Challenge
- Team KAIST, composed of students from the labs of Professor Jinwhan Kim of the Department of Mechanical Engineering and Professor Hyunchul Shim of the School of Electrical and Engineering, came through the challenge as the first runner-up winning the prize money totaling up to $650,000 (KRW 860 million).
- Successfully led the autonomous collaboration of unmanned aerial and maritime vehicles using cutting-edge robotics and AI technology through to the final round of the competition held in Abu Dhabi from January 10 to February 6, 2024.
KAIST (President Kwang-Hyung Lee), reported on the 8th that Team KAIST, led by students from the labs of Professor Jinwhan Kim of the Department of Mechanical Engineering and Professor Hyunchul Shim of the School of Electrical Engineering, with Pablo Aviation as a partner, won a total prize money of $650,000 (KRW 860 million) at the Maritime Grand Challenge by the Mohamed Bin Zayed International Robotics Challenge (MBZIRC), finishing first runner-up.
This competition, which is the largest ever robotics competition held over water, is sponsored by the government of the United Arab Emirates and organized by ASPIRE, an organization under the Abu Dhabi Ministry of Science, with a total prize money of $3 million.
In the competition, which started at the end of 2021, 52 teams from around the world participated and five teams were selected to go on to the finals in February 2023 after going through the first and second stages of screening. The final round was held from January 10 to February 6, 2024, using actual unmanned ships and drones in a secluded sea area of 10 km2 off the coast of Abu Dhabi, the capital of the United Arab Emirates. A total of 18 KAIST students and Professor Jinwhan Kim and Professor Hyunchul Shim took part in this competition at the location at Abu Dhabi.
Team KAIST will receive $500,000 in prize money for taking second place in the final, and the team’s prize money totals up to $650,000 including $150,000 that was as special midterm award for finalists.
The final mission scenario is to find the target vessel on the run carrying illegal cargoes among many ships moving within the GPS-disabled marine surface, and inspect the deck for two different types of stolen cargo to recover them using the aerial vehicle to bring the small cargo and the robot manipulator topped on an unmanned ship to retrieve the larger one. The true aim of the mission is to complete it through autonomous collaboration of the unmanned ship and the aerial vehicle without human intervention throughout the entire mission process. In particular, since GPS cannot be used in this competition due to regulations, Professor Jinwhan Kim's research team developed autonomous operation techniques for unmanned ships, including searching and navigating methods using maritime radar, and Professor Hyunchul Shim's research team developed video-based navigation and a technology to combine a small autonomous robot with a drone.
The final mission is to retrieve cargo on board a ship fleeing at sea through autonomous collaboration between unmanned ships and unmanned aerial vehicles without human intervention. The overall mission consists the first stage of conducting the inspection to find the target ship among several ships moving at sea and the second stage of conducting the intervention mission to retrieve the cargoes on the deck of the ship. Each team was given a total of three opportunities, and the team that completed the highest-level mission in the shortest time during the three attempts received the highest score.
In the first attempt, KAIST was the only team to succeed in the first stage search mission, but the competition began in earnest as the Croatian team also completed the first stage mission in the second attempt. As the competition schedule was delayed due to strong winds and high waves that continued for several days, the organizers decided to hold the finals with the three teams, including the Team KAIST and the team from Croatia’s the University of Zagreb, which completed the first stage of the mission, and Team Fly-Eagle, a team of researcher from China and UAE that partially completed the first stage. The three teams were given the chance to proceed to the finals and try for the third attempt, and in the final competition, the Croatian team won, KAIST took the second place, and the combined team of UAE-China combined team took the third place. The final prize to be given for the winning team is set at $2 million with $500,000 for the runner-up team, and $250,000 for the third-place.
Professor Jinwhan Kim of the Department of Mechanical Engineering, who served as the advisor for Team KAIST, said, “I would like to express my gratitude and congratulations to the students who put in a huge academic and physical efforts in preparing for the competition over the past two years. I feel rewarded because, regardless of the results, every bit of efforts put into this up to this point will become the base of their confidence and a valuable asset in their growth into a great researcher.” Sol Han, a doctoral student in mechanical engineering who served as the team leader, said, “I am disappointed of how narrowly we missed out on winning at the end, but I am satisfied with the significance of the output we’ve got and I am grateful to the team members who worked hard together for that.”
HD Hyundai, Rainbow Robotics, Avikus, and FIMS also participated as sponsors for Team KAIST's campaign.
2024.02.09 View 19872 -
Professor Joseph J. Lim of KAIST receives the Best System Paper Award from RSS 2023, First in Korea
- Professor Joseph J. Lim from the Kim Jaechul Graduate School of AI at KAIST and his team receive an award for the most outstanding paper in the implementation of robot systems.
- Professor Lim works on AI-based perception, reasoning, and sequential decision-making to develop systems capable of intelligent decision-making, including robot learning
< Photo 1. RSS2023 Best System Paper Award Presentation >
The team of Professor Joseph J. Lim from the Kim Jaechul Graduate School of AI at KAIST has been honored with the 'Best System Paper Award' at "Robotics: Science and Systems (RSS) 2023".
The RSS conference is globally recognized as a leading event for showcasing the latest discoveries and advancements in the field of robotics. It is a venue where the greatest minds in robotics engineering and robot learning come together to share their research breakthroughs. The RSS Best System Paper Award is a prestigious honor granted to a paper that excels in presenting real-world robot system implementation and experimental results.
< Photo 2. Professor Joseph J. Lim of Kim Jaechul Graduate School of AI at KAIST >
The team led by Professor Lim, including two Master's students and an alumnus (soon to be appointed at Yonsei University), received the prestigious RSS Best System Paper Award, making it the first-ever achievement for a Korean and for a domestic institution.
< Photo 3. Certificate of the Best System Paper Award presented at RSS 2023 >
This award is especially meaningful considering the broader challenges in the field. Although recent progress in artificial intelligence and deep learning algorithms has resulted in numerous breakthroughs in robotics, most of these achievements have been confined to relatively simple and short tasks, like walking or pick-and-place. Moreover, tasks are typically performed in simulated environments rather than dealing with more complex, long-horizon real-world tasks such as factory operations or household chores. These limitations primarily stem from the considerable challenge of acquiring data required to develop and validate learning-based AI techniques, particularly in real-world complex tasks.
In light of these challenges, this paper introduced a benchmark that employs 3D printing to simplify the reproduction of furniture assembly tasks in real-world environments. Furthermore, it proposed a standard benchmark for the development and comparison of algorithms for complex and long-horizon tasks, supported by teleoperation data. Ultimately, the paper suggests a new research direction of addressing complex and long-horizon tasks and encourages diverse advancements in research by facilitating reproducible experiments in real-world environments.
Professor Lim underscored the growing potential for integrating robots into daily life, driven by an aging population and an increase in single-person households. As robots become part of everyday life, testing their performance in real-world scenarios becomes increasingly crucial. He hoped this research would serve as a cornerstone for future studies in this field.
The Master's students, Minho Heo and Doohyun Lee, from the Kim Jaechul Graduate School of AI at KAIST, also shared their aspirations to become global researchers in the domain of robot learning. Meanwhile, the alumnus of Professor Lim's research lab, Dr. Youngwoon Lee, is set to be appointed to the Graduate School of AI at Yonsei University and will continue pursuing research in robot learning.
Paper title: Furniture Bench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation. Robotics: Science and Systems.
< Image. Conceptual Summary of the 3D Printing Technology >
2023.07.31 View 15540 -
KAIST debuts “DreamWaQer” - a quadrupedal robot that can walk in the dark
- The team led by Professor Hyun Myung of the School of Electrical Engineering developed “DreamWaQ”, a deep reinforcement learning-based walking robot control technology that can walk in an atypical environment without visual and/or tactile information
- Utilization of “DreamWaQ” technology can enable mass production of various types of “DreamWaQers”
- Expected to be used in exploration of atypical environment involving unique circumstances such as disasters by fire.
A team of Korean engineering researchers has developed a quadrupedal robot technology that can climb up and down the steps and moves without falling over in uneven environments such as tree roots without the help of visual or tactile sensors even in disastrous situations in which visual confirmation is impeded due to darkness or thick smoke from the flames.
KAIST (President Kwang Hyung Lee) announced on the 29th of March that Professor Hyun Myung's research team at the Urban Robotics Lab in the School of Electrical Engineering developed a walking robot control technology that enables robust 'blind locomotion' in various atypical environments.
< (From left) Prof. Hyun Myung, Doctoral Candidates I Made Aswin Nahrendra, Byeongho Yu, and Minho Oh. In the foreground is the DreamWaQer, a quadrupedal robot equipped with DreamWaQ technology. >
The KAIST research team developed "DreamWaQ" technology, which was named so as it enables walking robots to move about even in the dark, just as a person can walk without visual help fresh out of bed and going to the bathroom in the dark. With this technology installed atop any legged robots, it will be possible to create various types of "DreamWaQers".
Existing walking robot controllers are based on kinematics and/or dynamics models. This is expressed as a model-based control method. In particular, on atypical environments like the open, uneven fields, it is necessary to obtain the feature information of the terrain more quickly in order to maintain stability as it walks. However, it has been shown to depend heavily on the cognitive ability to survey the surrounding environment.
In contrast, the controller developed by Professor Hyun Myung's research team based on deep reinforcement learning (RL) methods can quickly calculate appropriate control commands for each motor of the walking robot through data of various environments obtained from the simulator. Whereas the existing controllers that learned from simulations required a separate re-orchestration to make it work with an actual robot, this controller developed by the research team is expected to be easily applied to various walking robots because it does not require an additional tuning process.
DreamWaQ, the controller developed by the research team, is largely composed of a context estimation network that estimates the ground and robot information and a policy network that computes control commands. The context-aided estimator network estimates the ground information implicitly and the robot’s status explicitly through inertial information and joint information. This information is fed into the policy network to be used to generate optimal control commands. Both networks are learned together in the simulation.
While the context-aided estimator network is learned through supervised learning, the policy network is learned through an actor-critic architecture, a deep RL methodology. The actor network can only implicitly infer surrounding terrain information. In the simulation, the surrounding terrain information is known, and the critic, or the value network, that has the exact terrain information evaluates the policy of the actor network.
This whole learning process takes only about an hour in a GPU-enabled PC, and the actual robot is equipped with only the network of learned actors. Without looking at the surrounding terrain, it goes through the process of imagining which environment is similar to one of the various environments learned in the simulation using only the inertial sensor (IMU) inside the robot and the measurement of joint angles. If it suddenly encounters an offset, such as a staircase, it will not know until its foot touches the step, but it will quickly draw up terrain information the moment its foot touches the surface. Then the control command suitable for the estimated terrain information is transmitted to each motor, enabling rapidly adapted walking.
The DreamWaQer robot walked not only in the laboratory environment, but also in an outdoor environment around the campus with many curbs and speed bumps, and over a field with many tree roots and gravel, demonstrating its abilities by overcoming a staircase with a difference of a height that is two-thirds of its body. In addition, regardless of the environment, the research team confirmed that it was capable of stable walking ranging from a slow speed of 0.3 m/s to a rather fast speed of 1.0 m/s.
The results of this study were produced by a student in doctorate course, I Made Aswin Nahrendra, as the first author, and his colleague Byeongho Yu as a co-author. It has been accepted to be presented at the upcoming IEEE International Conference on Robotics and Automation (ICRA) scheduled to be held in London at the end of May. (Paper title: DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning)
The videos of the walking robot DreamWaQer equipped with the developed DreamWaQ can be found at the address below.
Main Introduction: https://youtu.be/JC1_bnTxPiQ Experiment Sketches: https://youtu.be/mhUUZVbeDA0
Meanwhile, this research was carried out with the support from the Robot Industry Core Technology Development Program of the Ministry of Trade, Industry and Energy (MOTIE). (Task title: Development of Mobile Intelligence SW for Autonomous Navigation of Legged Robots in Dynamic and Atypical Environments for Real Application)
< Figure 1. Overview of DreamWaQ, a controller developed by this research team. This network consists of an estimator network that learns implicit and explicit estimates together, a policy network that acts as a controller, and a value network that provides guides to the policies during training. When implemented in a real robot, only the estimator and policy network are used. Both networks run in less than 1 ms on the robot's on-board computer. >
< Figure 2. Since the estimator can implicitly estimate the ground information as the foot touches the surface, it is possible to adapt quickly to rapidly changing ground conditions. >
< Figure 3. Results showing that even a small walking robot was able to overcome steps with height differences of about 20cm. >
2023.05.18 View 16623