This technology relates to an elastic unit capable of adjusting elastic force and elastic curves, and its operating method. It involves a technology that varies the stiffness characteristics themselves through a plurality of elastic control modules.
Conventional elastic members have fixed stiffness, requiring parts to be replaced whenever the intended use changes. Furthermore, adjusting the elastic curve—the displacement-load curve—in addition to the magnitude of the elastic force, has been even more difficult.
This technology simultaneously adjusts elastic force and elastic curves by combining elastic and inelastic bands and controlling the position of the fixing unit. It can be applied to various products, such as passive wearable robots and training equipment.
This invention was developed with support from the Ministry of Science and ICT for the development of machine learning and extended reality for high-speed mutual adaptation between users and wearable robots; the Korea Forest Service for the development of deep learning-integrated smart wearable suits for forest worker muscle assistance, injury prevention, and work efficiency improvement; and the Ministry of Trade, Industry and Energy for the development of human-augmentation hybrid robot suits capable of safe 7-second 100m sprints and comfortable 12-hour wear.
This technology relates to a gas supply system and operating method for driving pneumatic actuators, utilizing the vaporization of liquid nitrogen to supply high-pressure gas to wearable pneumatic actuators.
Existing pneumatic drive systems for wearable robots required compressors and large-capacity tanks, resulting in heavy weight, bulky volume, complex structures, and high manufacturing costs.
By incorporating a liquefied gas chamber and a vaporized gas discharge line, and utilizing waste heat to accelerate vaporization, this technology achieves lightweight, high-output pneumatic actuation while preventing actuator damage to enhance efficiency and safety.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of a human-augmentation hybrid robot suit capable of a 100m sprint in 7 seconds and comfortable 12-hour wear.
This technology features a gait assistance robot where the upper and lower leg units are connected by a knee joint unit, and the footplate is connected via an ankle joint unit. It utilizes intent-sensing sensors installed on the lower leg unit to instantly detect the wearer's gait intent based on muscle movement.
Existing gait assistance devices have struggled to accurately and quickly identify a user's gait intent. Furthermore, they often suffer from high noise levels, significant power consumption, and joint stiffness, making them ineffective for supporting patients in the early stages of rehabilitation.
This technology proposes a method that provides immediate assistance by combining intent-sensing sensors, which directly detect muscle movement, with a non-powered propulsion module. It can be applied to the rehabilitation of patients with central nervous system disorders, such as stroke, supporting natural gait tailored to the patient's intent while minimizing noise and power consumption.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of a machine learning-based lower limb rehabilitation robot system customized for stroke and Parkinson's patients.
This technology is a control method for scanning the 3D shape of an object by moving an underwater robot, equipped with a camera and a laser projector that emits a line laser at an angle, vertically between the minimum height required for object imaging and the maximum height for laser alignment, while simultaneously rotating it.
Existing stereo vision methods require high-performance computing and lighting, while sonar methods rely on expensive sensors, increasing manufacturing costs. Furthermore, these methods face challenges in achieving precise height control and resolution optimization for high-resolution 3D scanning.
This technology proposes a method of acquiring data with higher resolution toward the outer edges of an object by maintaining a constant tilt of the line laser while controlling rotation continuously or intermittently as the height descends. It can be applied to marine structure inspection and underwater terrain surveying, enabling high-resolution 3D scanning using only low-cost equipment.
This invention was developed with support from the Smart Underwater Tunnel System Research Center of the Ministry of Science and ICT.
This technology is a torque measurement system that precisely estimates joint torque by modeling and compensating for mechanical eccentricity errors within the reducer in a dual-encoder system—using both input and output encoders—and calculating the torsion angle from the angular deviation that occurs under load.
Existing robot joint torque measurement methods have faced structural limitations, such as the high cost of dedicated force/torque sensors, reduced joint stiffness in strain-gauge-based systems, and the low accuracy and difficulty of modeling reducer friction in current-based methods.
This technology proposes a method that models and stores mechanical eccentricity errors under no-load conditions using functions such as polynomials or Fourier series. During operation, it subtracts the compensation function value from the angular deviation to derive the pure torsion angle, which is then multiplied by the joint stiffness to calculate torque. It serves as an innovative solution for collaborative robots and precision assembly equipment, enabling precise force control without the need for expensive torque sensors.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of deep reinforcement learning-based collaborative technology capable of intelligently responding to unstructured work environments, such as assembly tasks.
This technology is a self-supervised mobile robot that converts 3D point cloud data into grid-based elevation maps, extracts multiple terrain features, and generates an AI model to determine traversability through a self-learning algorithm.
Existing manual labeling methods are costly, simulation data often differs from real-world environments, and simple threshold-based rules struggle to provide precise traversability assessments in complex urban settings.
This technology proposes a method that initializes positive samples from previous driving trajectories and negative samples from grids exceeding thresholds, then iteratively refines the model by reclassifying data based on the classifier's inference probability. This allows the model to improve its accuracy autonomously without human manual labeling. It can be applied to outdoor delivery and patrol robots, providing an economical solution that adapts to new environments without the need for separate data collection.
This technology is a laparoscopic camera control robot and a method for adjusting the camera view that uses AI algorithms to analyze real-time laparoscopic surgical footage. It autonomously controls the optimal camera perspective by recognizing surgical instruments, anatomical structures, and surgical actions.
The quality of laparoscopic camera operation has historically been inconsistent, depending on the skill level and fatigue of the surgical assistant. Furthermore, manual operation methods often lead to interruptions in the surgeon's workflow and a decrease in concentration.
This technology proposes a method that adjusts the camera center based on the position of surgical instruments within the laparoscopic video, corrects screen tilt by analyzing anatomical structures and environmental data, and automatically performs zoom-in and zoom-out functions based on the analysis of surgical actions. Applicable to all types of laparoscopic surgery, it reduces reliance on assistant personnel while simultaneously enhancing the surgeon's focus and the overall quality of the procedure.
This invention was developed with support from the Ministry of Science and ICT for the development of an automated rectal cancer surgery stage recognition system based on deep learning analysis of surgical video data.
This technology is a magnetic field synthesis control device that forms a magnetic field of a specific direction and intensity at a desired location by controlling the current applied to multiple coils. It determines the optimal current command within the rated current limit using a minimum infinity-norm current solution.
Previously, limitations in coil rated current often resulted in reduced synthetic magnetic field strength or unintended deviations in direction.
This technology proposes a method that calculates a first current command using the least squares method and a second current command that minimizes the infinity norm, determining the optimal current command within the rated current limit. This enables stable control that maximizes magnetic field synthesis performance without exceeding coil ratings. It can be utilized as a core control technology to maximize coil performance in fields requiring precise magnetic field control, such as magnetically driven microrobots, precision medical devices, and magnetic levitation systems.
This technology is a soft actuator and soft gripper that operates by injecting fluid into a flexible, zigzag-folded chamber to induce expansion. It achieves both linear deployment and bending motions by physically controlling the deployment angle through deployment limiters positioned between the folds.
Pneumatic soft robots have historically faced issues with large footprints due to internal chamber design and a tendency to sag under their own weight when not in operation.
By applying an origami-inspired structure, this technology minimizes size when not in use and utilizes fixed deployment limiters between the folding surfaces to restrict expansion in specific directions during fluid injection. This allows for the control of complex deployment and bending motions within a single actuator. It is suitable for applications in logistics automation, medical assistive devices, and end-effectors for collaborative robots, and is particularly advantageous for equipment where space efficiency is critical due to its foldable, compact storage design.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of collaborative assistive robot arms using foldable hybrid soft robot technology.
This technology is a longitudinally deployable vacuum suction cup that automatically deploys and grips objects by adapting to their position and orientation without the need for separate sensing or control, utilizing a mechanism that retracts the gripper body using vacuum pump negative pressure and expands it through external atmospheric pressure.
Conventional rigid cylindrical grippers cannot grip tilted objects, while standard bellows-type grippers are limited to objects at distances shorter than their initial length, and both require additional equipment to accurately detect the position and angle of objects in unstructured environments.
This technology proposes a system combining a pneumatic control system using a vacuum pump and a three-way valve, a deployable gripper body made of flexible polymer, and an external spring positioned between the body and an internal hose. This allows the gripper to automatically retract and generate gripping force upon contact without sensor feedback. It enables gripping without a separate vision system in environments where object shapes and placements are inconsistent, such as logistics picking, food packaging, and agricultural sorting, significantly reducing the implementation costs of automated equipment.
This invention was developed with support from the Human-Centered Soft Robot Technology Research Center of the Ministry of Science and ICT, and the development of collaborative assistive robot arms using foldable hybrid-actuated soft robot technology from the Ministry of Trade, Industry and Energy.
This technology utilizes two groups of steering wires arranged in helical patterns in opposite directions along the backbone of a soft robot. By alternating the distance of each wire from the backbone's center, it cancels out unintended tension interference caused by wire length changes during backbone bending.
In soft mechanisms, relative displacement between the steering wires and the backbone during bending often leads to unintended tension on the end-effector, resulting in reduced steering precision.
This technology features steering wire groups with opposing helical structures placed on the outer surface or inside of a longitudinally extending backbone. By alternating their positions between the inner and outer sides at each helical period, the system mechanically cancels out the length differences caused by backbone bending. Applicable to surgical soft robots, endoscopes, and inspection robots for confined spaces, it enhances steering precision by neutralizing unintended tension during bending.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of robot task control technology capable of grasping, manipulating, and using tools on various objects in daily environments based on multimodal perception.
This technology is a soft robotic gripper composed of a multi-layer elastomer sensor skin and a joint utilizing optical waveguide modes. It employs a multi-layer thin-film sensor skin (bottom, core, and top layers) to sense contact force with objects, and incorporates a flexible joint structure with an embedded core sensor that uses optical waveguide modes to measure the bending angle of the joint.
Conventional SDM-based soft grippers involve complex and time-consuming manufacturing processes and lack an integrated sensing structure capable of simultaneously and precisely measuring both contact force and finger bending angles.
This technology utilizes 3D-printed rigid molds to create soft molds, enabling the integrated manufacturing of elastomer-based phalanges, multi-layer sensor skins, and optical waveguide joints. The sensor skin is formed with a multi-layer structure of varying flexibility to detect contact force, while the joint combines a core sensor and an outer shell to detect bending angles. Applicable to logistics picking, precision assembly, and service robots, this solution enables simultaneous measurement of contact force and bending angles while simplifying production through soft molding.
This invention was developed with support from the Ministry of Trade, Industry and Energy for inflatable soft robotic arm technology for the care of the elderly and patients.
This technology is a wearable knee assist device that combines a link structure mounted on the wearer's lower limb with an actuator. It minimizes resistance during walking by overlapping the links and supports loads with minimal power during standing by utilizing the elasticity and mechanical geometric configuration of the links.
Conventional wearable knee assist devices rely entirely on motor drive, leading to high battery consumption, the need for frequent charging, and reduced operational efficiency due to battery capacity limitations.
By combining an actuator located at the joint with a variable-length link equipped with extension-direction elasticity, this technology eliminates actuator resistance in walking mode and minimizes torque load through the geometric configuration of the links in support mode. It is applicable to muscle strength assistance in industrial settings and gait support for the elderly, ensuring practicality for long-term wear without the burden of frequent charging.
This technology is an interface system for human-robot interaction that acquires electromyography (EMG) signals using a metal-rubber electrode array—composed of elastic material and metal particles—integrated into a body-hugging wearable device. It utilizes ultra-short amplifiers within metal shielding to eliminate noise and controls robotic devices based on measured waveforms and signal propagation path information.
Limitations in human neural potential measurement technology have made it difficult to implement accurate bidirectional human-robot interfaces, particularly resulting in low data precision in environments requiring high-sensitivity measurement, such as rehabilitation therapy and virtual reality.
This technology enhances body contact through elastic metal-rubber electrodes infused with metal particles, suppresses noise with metal shielding, and determines the temporal and spatial propagation paths of EMG waveforms in real time. It can be applied to rehabilitation therapy, prosthetic control, and virtual reality interaction, significantly improving the reliability of human-robot interaction through precise biosignal acquisition.
This technology relates to a spinal assist unit and a human-spine-mimicking kyphosis assistive device, specifically a wearable device designed to correct and support spinal curvature while the user is in an upright position.
Conventional spinal orthotics are rigid, significantly restricting torso movement and causing discomfort in daily life. Furthermore, they are difficult to adapt to individual body types, making long-term wear challenging.
This technology utilizes a semi-active approach, connecting multiple spinal assist units to mimic the human spine and adjusting tension via a wire-driven system, allowing for customized support tailored to the wearer's height, width, and weight.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of a human-augmentation hybrid robot suit capable of safe 100m sprints in 7 seconds and comfortable 12-hour wear, as well as the development of core technologies for string-twist-based, compact, lightweight, high-performance, and highly durable safe drive modules utilizing string surface reinforcement, variable radius pulleys, and hybrid drive control.
