Surgical Bed Integrated with Magnetic Field Control and Imaging Systems

This technology features magnetic induction coils arranged radially beneath the patient bed. By generating a variable magnetic field, it enables wireless steering and propulsion of surgical microrobots or catheters inserted into the body.

Conventional setups operate X-ray imaging equipment and magnetic guidance devices separately, leading to bulky hardware, poor space utilization, and hardware interference that limits surgical precision.

This technology integrates the X-ray imaging unit and magnetic guidance system into the surgical bed. The magnetic induction coils are designed for radial arrangement and mobility, allowing for a compact system that performs precise magnetic steering under real-time image guidance. Applicable to surgical robots, interventional procedure systems, and medical automation, it provides real-time visualization of the affected area, minimizes the size of the magnetic guidance components, and maximizes space efficiency to enhance surgical workflow.

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Key Features:

• An imaging unit (120) comprising: an X-ray emitter (121); an X-ray receiver (122) positioned at a set distance from and facing the X-ray emitter (121) to receive X-rays emitted therefrom; an imaging support (123) with the X-ray emitter (121) coupled to one side and the X-ray receiver (122) coupled to the other; and an imaging movement mechanism (124) formed between the imaging support (123) and the main body (110).
• A bed unit (130) comprising: a bed (131) positioned between the X-ray emitter (121) and the X-ray receiver (122) to support a patient; a bed movement mechanism (132) formed between the main body (110) and the bed (131); a magnetic induction unit (133) provided beneath the bed (131) to induce a magnetic field; and a magnetic induction movement mechanism (134) formed between the underside of the bed (131) and the magnetic induction unit (133).
• A bed unit (130) comprising a magnetic induction unit (133) provided beneath the bed (131) to induce a magnetic field, and a magnetic induction movement mechanism (134) formed between the underside of the bed (131) and the magnetic induction unit (133).
• A surgical bed integrated with a magnetic field control and imaging system, wherein the magnetic induction unit (133) is characterized by a plurality of magnetic induction coils (133a) arranged radially at a set distance around a central reference point.

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This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of a microrobotic system for the treatment of chronic total occlusion in myocardial infarction.

Parameter Estimation Method for Industrial Robots via Fast and Robust Trajectory Design

This technology improves parameter identification efficiency by collecting robot position and torque data, removing noise using zero-phase low-pass filters and the RLOESS algorithm, and generating optimized excitation trajectories that reduce computational complexity through the use of Hadamard's inequality.

Conventional methods for designing excitation trajectories for robot dynamic parameter estimation have faced challenges with high optimization computational complexity and long processing times as the number of parameters increases.

This technology introduces optimized signal processing steps (zero-phase low-pass filtering and RLOESS smoothing) for position, velocity, acceleration, and torque data, and implements an excitation trajectory generation algorithm with high computational efficiency by applying Hadamard's inequality during the determinant optimization process. Applicable to industrial robots and automation systems, it enhances the accuracy of dynamic parameter estimation while reducing complexity and operational time for parameter optimization.

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Key Features:

• Step (S140) of optimizing the trajectory used for estimating the robot's dynamic parameters by applying a least-squares parameter estimator to the results obtained from dynamic estimation modeling.
• Step (S110) of collecting position or torque data of a robot in a parameter estimation method via trajectory design.
• Signal processing step (S120) of reducing noise in the collected data to improve the accuracy of the data.
• Step (S130) of performing dynamic estimation modeling of the robot.

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This invention was developed with support from the Ministry of Science, ICT and Future Planning for the development of renewable energy and intelligent robot convergence technology.

Movement Path Control Device Using Distance Difference and Sum Calculation of Boundary Signal Generators

This technology is a movement path control device that receives signals from multiple signal generators located on a boundary line to calculate the distance between an object and each signal generator, and analyzes changes in distance differences and sums to determine the object's angle of incidence and whether it has crossed the boundary.

Existing systems have struggled to maintain stable work zones because it is difficult to determine and control in real-time when an autonomous object deviates from a designated boundary.

This technology proposes a method that determines if the angle of incidence relative to the boundary is perpendicular based on changes in the distance difference between two signal generators, and detects boundary deviation based on changes in the distance sum. It can be applied to robotic lawnmowers and outdoor autonomous work machines to accurately maintain work zones without the need for physical fences.

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Key Features:

• A signal receiver that receives signals from multiple signal generators located on a boundary line
• A distance calculator that calculates the distance to an object using signals received from the first and second signal generators
• A first processing unit that calculates the change in the distance difference between the two signal generators to determine the object's angle of incidence relative to the boundary
• A configuration that determines whether an object has deviated from the boundary using the change in the sum of distances between the two signal generators

Position Estimation Device for Underwater Robotic Hydraulic Manipulators Using Joint Hydrostatic Pressure Differential Measurement

This technology is a device that estimates the 3D position of an end-effector by measuring the hydrostatic pressure differential at the joints of an underwater robotic hydraulic manipulator to calculate the vertical displacement of each joint link, combined with yaw angle data measured by a compass.

In turbid underwater environments, camera-based position estimation is difficult, and conventional rotary encoder methods are unsuitable for the harsh operating conditions of hydraulic manipulators, leading to challenges in achieving precise position tracking.

This technology proposes a method that calculates vertical displacement using hydrostatic pressure differentials and the specific weight of water, determines the pitch angle and horizontal displacement of joint links based on these values, and derives the roll angle using an offset pressure gauge. It can be applied to underwater work robots and offshore plant maintenance, enabling accurate tracking of manipulator posture even in environments with zero visibility.

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Key Features:

• Multiple pressure gauges installed at the joint connections of the hydraulic manipulator's multiple joint links to measure hydrostatic pressure
• A compass installed on the first joint link connected to the base frame to measure the yaw angle of the manipulator
• A configuration that calculates the vertical displacement of each joint link based on the hydrostatic pressure differential between both ends of the link
• An end-position calculation unit that determines the position of the end-effector based on vertical displacement, link length, and yaw angle

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This invention was developed with support from the Smart Underwater Tunnel System Research Center of the Ministry of Science and ICT.

Collision Avoidance Technology for Multiple Mobile Robots via Priority-Based Path Recalculation

This technology generates paths for multiple mobile robots based on driving priority. When a collision is predicted during operation, it recalculates the path of the lower-priority robot to prevent deadlocks in dynamic environments and maintain optimal routing.

Existing decentralized path planning methods typically address collisions or deadlocks by modifying paths or simply adjusting speed, which often fails to effectively manage mutual path interference or resolve persistent deadlocks.

This technology establishes driving priority by integrating initial priority, path cost, and mission importance. When a collision is predicted, it recalculates the path of the lower-priority robot by accounting for node and edge occupancy time. Applicable to multi-robot operations in logistics warehouses and smart factories, it fundamentally prevents line stoppages caused by deadlocks and maximizes overall throughput.

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Key Features:

• Registering the navigation map of the space where multiple mobile robots operate into the system
• Registering the initial priority, starting point, and destination for each mobile robot
• Generating paths for each robot sequentially based on their initial priority
• Recalculating the path of the lower-priority robot by considering occupancy time information when a collision is predicted

EEG-based wearable robot control technology with head motion artifact removal

This technology is an EEG-based wearable robot control device and method that filters out highly correlated components by linking head motion sensor data with independent component analysis (ICA) of EEG signals to remove artifacts caused by head movement, thereby generating training data for classifying gait intention based on pure EEG signals.

Conventional technologies rely on multiple sensors, such as foot pressure sensors, to determine gait intention, which compromises durability. Furthermore, they face technical limitations in accurately reflecting user intent due to noise interference caused by head movement during EEG measurement.

This technology proposes a method of collecting EEG signals per movement unit using head motion sensors and EEG detectors, identifying and removing components highly correlated with head movement through independent component analysis, and then extracting features from the remaining signals. It can be applied to lower-limb rehabilitation and gait assistance robots, accurately detecting a user's gait intention using only EEG signals without the need for additional sensors.

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Key Features:

• Receiving information on the user's head movement and the wearable robot induced by the user
• Collecting the user's EEG signals detected during movement and storing them by movement unit
• Separating the collected EEG signals into multiple independent components through independent component analysis
• Generating training data by removing independent components that have a correlation with head movement information above a threshold value

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This invention was developed with the support of the Ministry of Science, ICT and Future Planning for the development of vehicle driving and hazard recognition technology through automated brain signal analysis.

Autonomous Mobile Robot System Integrating Path Block Segmentation and Speed Control

This technology controls the navigation of autonomous mobile robots based on path information defined in blocks. It defines surfaces and task markers—including outlines, ways, and speed data—within each path block to perform obstacle detection, collision avoidance, and speed regulation.

Conventional magnetic tape guidance systems incur high reinstallation costs when factory layouts change. Furthermore, they struggle with efficient speed control and flexible task execution because central control systems cannot account for the real-time status of individual robots.

This technology segments movement paths into blocks, allowing users to configure routes and tasks via an interface. The central system aggregates status information from individual robots to calculate speed adjustments or detours in real-time based on estimated arrival times. Applicable to automated transport in factories and warehouses, it enables flexible responses to facility changes and continuous improvements in operational efficiency.

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Key Features:

• A transport vehicle drive unit equipped with a sensor module and a drive motor for the vehicle body
• A transport vehicle control unit connected to the sensor module and drive unit to regulate the operation of the drive motor
• A configuration that sets and inputs movement paths in block units containing outlines, ways, surfaces, and task markers
• A system control unit that aggregates operational data from each vehicle to manage speed or detours based on estimated arrival times

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This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of logistics robot systems applicable to wide-area hospital environments.

SLAM System for Mobile Robots Using Fused Vision and Motion Sensor Data

This technology is a SLAM system for mobile robots that improves localization accuracy by combining environmental feature points and spatial occupancy data extracted from vision sensors with movement data calculated from motion sensors using a probability-based data fusion technique.

When using vision sensors alone, issues such as motion blur during robot movement and decreased accuracy in dynamic environments often lead to cumulative errors in localization and mapping.

This technology proposes a modular SLAM architecture that includes a vision sensor processor, a motion sensor processor, and a third processor that re-estimates the robot's position by fusing this information using probability-based filters such as a Kalman filter. This allows for mutual compensation between sensors, suppressing error accumulation and enabling the creation of precise maps. It can be applied to various indoor autonomous driving applications, including cleaning robots, logistics robots, and service robots, significantly increasing the reliability of localization through sensor fusion.

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Key Features:

• Vision sensor including at least one of the following: monocular camera, stereo camera, laser sensor, or ultrasonic sensor
• Motion sensor including an accelerometer, gyroscope, encoder, etc., to acquire robot motion data and provide it for movement calculation
• Processor that estimates position using vision sensor data, calculates movement using motion data, and re-estimates position by fusing the two
• Mapping device that creates maps using the estimated position and feature point or spatial occupancy information

Cableless SOBW Surgical Device with Integrated Electric Actuation in the End Effector

This technology is an electrically driven SOBW-type surgical device that replaces the conventional mechanical cable-driven system in the end effector of a surgical robot, instead utilizing direct electrical power to perform gripping, pitching, and yawing motions through an integrated motor and gear structure.

In conventional surgical robots, the end effector is driven by cables, which leads to complex connection structures as the number of joints increases or the extension length grows. This results in issues such as backlash caused by long-distance transmission, as well as durability and precision problems due to cable stretching or breakage.

This technology proposes a method of directly placing motors, screw components, and gears inside the end effector to instantly convert electrical energy into mechanical energy. This allows for independent gripping, pitching, and yawing motions without the need for cables, thereby increasing control precision and achieving structural miniaturization. Applicable to the end effectors of laparoscopic surgical robots, it fundamentally resolves the backlash and durability issues associated with cable-driven systems while simultaneously improving the miniaturization and precision of surgical instruments.

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Key Features:

• A body section and an extension section connected at one end to the body to transmit electrical energy to the end effector
• An end effector formed at the other end of the extension section that converts electrical energy into mechanical energy
• An operating section formed by forceps including a first leg and a second leg, and a gripping mechanism that induces the gripping motion
• A pitching motor unit that converts electrical energy into rotational motion and a gear unit that induces the pitching motion of the operating section

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This invention was developed with support from the Ministry of Education, Science and Technology for research on the feasibility of developing next-generation laparoscopic surgical tools applying aerospace, electronic, and mechanical engineering.

Hemiplegia Rehabilitation Device Combining Contralateral Motion Synchronization and Visual Illusion

This technology is a hemiplegia rehabilitation device that measures the movement of a patient's unaffected limb using sensors such as motion capture, electromyography (EMG), and inertial measurement units (IMU). By analyzing this data in real time, it drives the joints of an exoskeleton robot worn on the hemiplegic side, enabling synchronized bilateral limb movement.

Conventional hemiplegia treatment often relies on simple, repetitive motions, resulting in low rehabilitation efficiency. Existing wearable robots function primarily as simple assistive devices, which limits their ability to induce neuroplasticity and makes it difficult to implement systematic rehabilitation that leverages a patient's cognitive illusions.

This technology proposes a system that integrates a control unit—which receives motion data from the unaffected limb to drive the hemiplegic-side robot in real time—with a visual separation device, such as a screen or mirror, that blocks the view of the unaffected limb to make the patient perceive that their hemiplegic side is moving normally. This approach provides effective rehabilitation by inducing neuroplasticity. It can be used for the rehabilitation of stroke patients with hemiplegia, offering superior therapeutic outcomes compared to traditional repetitive training by combining visual illusion with robotic assistance to stimulate neuroplasticity.

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Key Features:

• An exoskeleton robot worn on the patient's hemiplegic side that drives joints in correspondence with the movement of the unaffected limb.
• A motion measurement unit that uses motion capture and sensors to measure the movement of the patient's unaffected limb in real time and transmits the data to the control unit.
• A control unit that receives the measured motion data of the unaffected limb and controls the robot to ensure the hemiplegic side moves accordingly.
• A screen or barrier that obscures the view of the unaffected limb while allowing the patient to see the movement of the hemiplegic side.

Passive prosthetic forearm with spatial four-bar linkage mimicking ulnar-radial rotation

This technology is a passive prosthetic arm that uses a spatial four-bar linkage structure to replicate the natural cross-rotation mechanism between the human ulna and radius. It captures the rotational movement of the residual limb and transmits it from the first axis (coupling) to the second and third axes, using a gear set to amplify the rotation and physically extend the range of motion of the wrist.

Existing electric motor-based prosthetics suffer from heavy weight and poor replication of natural human movement. Furthermore, patients with partial forearm amputations often face limitations in pronation and supination due to the loss of the natural ulnar-radial cross-rotation.

This technology features a coupling unit that converts the movement of the residual limb into rotation around a first axis, a base link corresponding to the ulna, and a four-bar linkage fastening structure. By using a rotation amplification unit composed of four types of gears, the input rotation is amplified and transmitted to the wrist, enabling passive movement that closely mimics the forearm rotation of a healthy individual. It can be applied to prosthetics, rehabilitation aids, and wearable devices, extending the range of wrist pronation and supination without the need for motors, thereby reducing both weight and cost.

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Key Features:

• A fastening unit that provides a second axis linked to the rotation of the first axis on the upper side of the other surface, and a third axis spaced at a predetermined distance from the second axis on the lower side of the other surface.
• A coupling unit attached to one end of the residual limb that generates rotation around the first axis through the pronation or supination movement of the arm.
• A base link that extends from the elbow area to the wrist area of the residual limb and is positioned on one side of the ulna.
• A prosthetic arm where the angle formed by a first virtual line, defined by the cross-sections of the first and second axes, and a second virtual line, defined by the cross-sections of the second and third axes, changes during movement.

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This invention was developed with support from the Ministry of Science, ICT and Future Planning for the development of biomimetic bionic arm mechanisms.

Precision assembly gripper for confined spaces combining telescopic legs and suction functionality

This technology features a body member and a pair of sliding leg members, integrating the telescopic function of the first leg with the suction capability of the second leg to create a precision gripping and assembly mechanism.

Conventional multi-jointed grippers are structurally unsuitable for installing electronic components in tight spaces, such as inside small mobile device cases, and relying solely on suction methods often results in poor positioning accuracy.

By combining the telescopic length adjustment of the first leg with the vacuum suction of the second leg, this technology performs a multi-stage gripping operation: it picks up and transports objects with a wide span, then reduces the leg spacing and length while maintaining suction to precisely seat components in confined areas. It can be applied to electronic component assembly, precision manufacturing, and small device automation, enhancing assembly accuracy by precisely positioning parts in tight spaces.

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Key Features:

• First and second leg members supported by a body member with adjustable distance between them
• A suction unit on the second leg member for picking up and securing objects, and a telescopic first leg member
• A structure where the leg members are supported by the body member and slide horizontally to adjust the distance between them
• The first leg member includes a support section attached to the body member and a telescopic section that extends and retracts from the support section

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This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of process technology, grippers, and assembly techniques for small, precision electronic component assembly in mobile IT products.

Brain-Computer Interface Training Device and System

This technology is a training device that rehabilitates motor nerves based on EEG by inducing a sense of body ownership, linking a model that mimics a specific part of the human body with a stimulation unit that provides physical feedback.

There have been challenges regarding motor impairment in patients with brain injuries, as well as limitations in existing virtual reality-based rehabilitation methods.

This technology provides a training system that uses joints and actuators to move a model mimicking a specific body part in a real-world environment, while simultaneously applying physical stimulation to both the actual body part and the model to induce neuroplasticity. It can be applied to rehabilitation training, gait assistance, and medical/welfare services, improving motor function in patients with movement disorders by providing feedback and promoting neuroplasticity.

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Key Features:

• A model unit comprising joints, actuators installed on the joints, and a main body connected to the actuators that can move in specific directions relative to the joints and is shaped to mimic a specific part of the human body.
• A model unit comprising a main body connected to an actuator that can move in specific directions relative to a joint and is shaped to mimic a specific part of the human body.
• A stimulation unit that provides stimulation to a portion of the main body and the corresponding specific part of the human body.
• A stimulation unit that provides stimulation to a specific part of the human body corresponding to a portion of the main body.

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This invention was developed with support from the Ministry of Science, ICT and Future Planning for brain mapping-based robot rehabilitation.

Layer Jamming Actuator for Multi-Degree-of-Freedom Postures

This technology relates to a layer jamming actuator, a drive system for wearable robots that varies stiffness through an enclosure structure capable of sliding and pivoting.

Conventional layer jamming actuator units have limitations in bending and tensile movement, making them difficult to use in various body postures.

This technology prevents interference and enables smooth operation by configuring each enclosure to slide and pivot relative to one another, making it highly effective for wearable robots that require multiple degrees of freedom.

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Key Features:

• An enclosure made of variable material designed to house a layer stack inside
• A layer stack consisting of multiple layers inside the enclosure, with stiffness varied through jamming
• A structure where each layer in the stack is configured to slide and rotate relative to one another
• Connecting layers provided on the top and bottom surfaces of adjacent layer stacks, linked by strings

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This invention was developed with support from the Ministry of Trade, Industry and Energy’s Engineering Specialized Graduate School Support Program (Plant Engineering), the Ministry of Science and ICT’s Bionic Hand Mechanism Development project, and the Ministry of Science and ICT’s Human-Centered Soft Robotics Technology Research Center.

Technology for 3D Reconstruction of Underwater Objects Using Ultrasonic Point Cloud Grouping and Polygon Reconstruction

This technology enables an underwater robot equipped with an ultrasonic camera to generate a 3D point cloud from image data acquired while moving around an object from multiple directions. It then groups the data by movement direction and reconstructs it into a 3D polygon through 2D projection and polygon calculation.

Existing ultrasonic camera methods have limitations in reproducing seafloor objects as realistic 3D shapes because they map 3D information onto a 2D plane.

This technology proposes a method to achieve high-precision 3D modeling by grouping point clouds acquired from multiple angles, performing maximum overlapping polygon calculations, and applying post-processing noise reduction. It can be applied to seafloor exploration, shipwreck searches, and marine structure diagnostics, providing near-realistic shape information even in high-turbidity environments.

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Key Features:

• Detecting objects located on the seafloor based on image data acquired from an ultrasonic camera
• Acquiring multiple sets of image data by moving in multiple directions relative to the object
• Analyzing the multiple sets of image data to calculate 3D point cloud data for the object
• Grouping point cloud data according to movement direction and implementing 3D polygons through polygon calculation

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This invention was developed with the support of the Smart Underwater Tunnel System Research Center of the Ministry of Science and ICT.