This technology is a hybrid mobile platform mechanism that combines driving wheels with track modules. By adjusting the angle of the track arms via motor power, the structure can be varied to ensure wheel contact on flat surfaces and track contact with the ground on rough terrain.
Conventional wheeled robots excel on flat surfaces but struggle with rough terrain and stairs. Tracked robots are advantageous for rough terrain but suffer from lower speed and energy efficiency on flat surfaces, while legged robots face challenges with complex control and stability.
This technology features a track transformation mechanism that adjusts the position of the track arms using a motor. On flat ground, the track arms are kept horizontal for wheel-based driving, while on rough terrain or stairs, the arms are raised to bring the tracks into contact with the ground, optimizing the driving mode. Applicable to logistics, service robots, and autonomous platforms, it enhances the adaptability and stability of specialized service robots on uneven terrain, thereby improving overall performance and energy efficiency.
This technology is an integrated location tracking and monitoring mechanism that tracks the positions of sensors worn by guardians and children via a sensor network composed of multiple relay sensors. A management server monitors the distance between them in real-time, and in the event of a child going missing, a safety robot is dispatched along the shortest path to the child's location to collect and transmit video and audio data.
Existing GPS-based technologies are unable to track locations in signal-shadowed areas such as indoors or underground, while RFID-based technologies have limitations due to short transmission ranges, requiring the dense installation of numerous readers and resulting in high physical infrastructure costs.
This technology works by having a group of relay sensors receive signals from sensors held by the guardian and the child, which are then transmitted to a management server that calculates their positions and measures the distance between them. If a child goes missing, the management server calculates the shortest path for a safety robot and issues a movement command, allowing the robot to arrive on-site to capture and transmit video and audio data. Applicable to logistics, service robots, and autonomous driving platforms, this system improves the efficiency and accuracy of child safety by providing real-time location tracking and early detection of potential missing child scenarios.
This technology is an autonomous driving path planning method that divides image space into cells to calculate the density of static and dynamic obstacles. It then performs hierarchical/non-hierarchical clustering and applies a genetic algorithm (GA) to generate obstacle-avoidance paths.
Existing genetic algorithm-based path planning focuses solely on finding the shortest path, leading to increased computational load as workspace size grows. Furthermore, it fails to adequately account for dynamic obstacle information, resulting in persistent collision risks during movement.
This technology converts images into grayscale occupancy (static) and brightness information (dynamic) to calculate density. It then reduces data complexity through k-means clustering and derives an optimal path by applying a genetic algorithm that integrates obstacle density, path distance, and penalties for infeasible paths into the fitness function. This improves routing performance by accounting for workspace size and dynamic obstacle information, making it suitable for applications in rehabilitation training, gait assistance, and medical/welfare services.
This technology improves steering performance and driving stability by integrating real-time robot distance sensor (laser/ultrasonic) data with camera video feeds, overlaying them on a remote controller display, and providing force or haptic (vibration motor) feedback to the joystick based on obstacles in the robot's vicinity.
Existing remote control systems rely on narrow camera fields of view and 2D video, making it difficult to accurately perceive depth between the robot and obstacles. This often leads to reduced operational efficiency, such as collisions or the robot becoming stuck during non-line-of-sight navigation.
This technology visualizes obstacle distance information by overlaying it onto the video feed. If the operator attempts to steer toward an obstacle within a set safety distance, a feedback control mechanism triggers a vibration motor (haptic) or braking system (force feedback) in the joystick to alert the operator. Applicable to rehabilitation training, gait assistance, and medical/welfare services, it enhances operability by providing wide-range situational awareness and haptic feedback, thereby reducing collisions and isolation in remote control scenarios.
This technology is a multi-robot control system based on a WPAN wireless network that performs auto-spacing and cooperative localization through a master-slave architecture. The master robot receives commands from a central controller and retransmits them to slave robots or issues self-generated commands, while the slave robots control their real-time movement based on the received commands and distance information.
When controlling multiple mobile units simultaneously in environments with poor communication infrastructure, such as disaster sites, there have been challenges regarding communication range limitations, radio frequency interference, and ensuring the sequentiality and accuracy of control signals.
This technology utilizes the WPAN (IEEE 802.15.4a) wireless protocol to establish a network between multiple robots and implements a distance-based control algorithm that measures distance information from other robots in real-time upon receiving an auto-spacing command, executing movement commands only when the distance exceeds a set value. It can be applied to industrial robots and automated systems, improving the control of multiple mobile units by enabling efficient communication and coordination between the robots and the central controller.
This technology measures the distance between three RF nodes arranged in an equilateral triangle on the top plate of a master robot and the RF node of a slave robot. By rotating the top plate, it identifies the point where the distances between specific nodes on the master robot and the slave robot become equal, then calculates the relative position of the slave robot using the resulting geometric triangulation and rotation angle.
Conventional technologies for swarm robot localization require the installation of expensive infrastructure or complex sensing devices, such as gyro and ultrasonic sensors, on each individual robot, leading to high data processing loads and increased system costs.
This technology equips the master robot with a rotating top plate and three RF nodes arranged in an equilateral triangle, while minimizing the hardware on the slave robot to just an RF node. Based on the rotation of the master robot's top plate and the distance information between nodes, the master robot precisely calculates the slave robot's position and issues formation commands. Applicable to robot gripping, precision measurement, and automated facilities, this approach minimizes data processing and hardware requirements for a large number of slave robots, thereby reducing overall system load and construction costs.
This invention was developed with support from the Ministry of Education, Science and Technology for the development of public safety smart monitoring and active response technologies.
This technology is a fuzzy logic-based control mechanism that calculates autonomous driving control values by combining positive fuzzy rules for target tracking with negative fuzzy rules for obstacle avoidance. It determines the optimal movement direction (avoidance angle) by applying Gaussian membership functions to obstacle location data detected by ultrasonic sensors and target point information input from a controller.
Conventional remote robot control systems rely on manual user operation, posing a high risk of collision if obstacles are not detected. Furthermore, the lack of integrated autonomous avoidance control technology reduces the reliability of remote operation.
This technology configures a control system that uses the distance and angle between the robot and the target point, as well as the robot and obstacles, as input variables. It applies positive and negative rules respectively, derives the fitness of each input fuzzy set based on mathematical formulas, and calculates the final movement avoidance angle through the computation of output fuzzy set fitness including additive offsets. Applicable to rehabilitation training, gait assistance, and medical/welfare services, it enables self-regulated obstacle avoidance, thereby enhancing the reliability of remote control in robot navigation.
This invention was developed with support from the Ministry of Education, Science and Technology's Biomimetic Robot Technology Development program.
This technology estimates a robot's base position by combining motor encoder and inertial sensor (gyroscope, accelerometer) data. It corrects cumulative errors by resetting the current position to specific coordinates when the robot passes through high-reliability reception zones (within 1.5m, -50dBm or higher) defined around pre-mapped Wi-Fi access points.
Positioning methods in indoor environments that rely solely on motor encoders and inertial sensors are vulnerable to external disturbances and struggle to resolve long-term cumulative errors. Furthermore, conventional methods that directly convert wireless LAN signal strength into distance information suffer from low precision due to signal instability caused by environmental factors.
This technology integrates a robot system, a wireless network system, and a positioning server to execute a position correction algorithm based on signal strength in proximity to access points. Specifically, it processes sensor data through a data fusion unit, switches to inertial sensor-based positioning during impacts, and resets position coordinates using signal strength thresholds near access points. Applicable to logistics transport, service robots, and autonomous platforms, it improves positioning accuracy by utilizing short-range wireless LAN signal strength for error correction.
This invention was developed with support from the Ministry of Education, Science and Technology for the development of renewable energy and intelligent robot convergence technology.
This technology is a power management system for mobile robots equipped with multiple energy sources, such as batteries, fuel cells, and solar cells. It features an integrated management mechanism that dynamically switches between energy sources and controls the return to automatic charging stations by monitoring remaining power levels and measuring the distance to chargers.
The limitations include the restricted operating time of single-battery mobile robots, which hinders continuous mission performance and necessitates frequent user intervention, as well as the lack of efficient switching and management when using multiple energy sources.
This technology incorporates BMS, FCMS, and SCMS within the robot's power management unit to independently monitor the status of each energy source. Through a wireless communication management unit, it calculates real-time data on remaining power and distance to the charger to determine mission feasibility, triggering automatic returns and energy source switching as needed. Applicable to robot gripping, precision measurement, and automated equipment, this system efficiently manages diverse power sources and provides stable, versatile power to robots, thereby extending the operational time of continuous pollution monitoring robots.
This invention was developed with support from the Ministry of Education, Science and Technology for the development of renewable energy-based intelligent robot convergence technology.
This technology is a wireless control system for an implantable helical microrobot that generates its own power to operate a light-emitting unit by acquiring induced electromotive force from an external magnetic field generator.
Conventional microrobots face limitations in performing therapeutic tasks and tracking their position within the human body due to the difficulty of providing a separate power supply for wireless operation.
This technology features a microrobot with a metallic head and a helical body that rotates and moves in response to an applied external magnetic field. During this process, it generates induced electromotive force from magnetic field changes to power a stacked LED (light-emitting unit). Applicable to industrial robots and automation systems, it improves the ability to position and perform therapeutic actions within the human body using induced electromotive force and wireless operation.
This invention was developed with support from the Ministry of Education, Science and Technology for the development of bio-mimetic biosensors and medical robot convergence technology.
This technology provides a method for multiple slave robots to collaboratively operate a valve using a jig. It features a control mechanism where robots measure valve dimensions to set gripper coordinate systems and then rotate the valve by alternately gripping the jig based on generated paths.
When a single robot lacks sufficient torque or the valve's rotation range exceeds the robot's workspace, remote control of a single unit is limited. Furthermore, manual remote operation of the entire process leads to high operator fatigue and reduced efficiency.
This technology utilizes two or more slave robots to generate motion paths for each unit through a collaborative and autonomous command generation device. While gripping the jig, the robots measure valve dimensions and use this data to rotate the valve by alternately gripping the jig. It includes a safety control function that halts path tracking if excessive force is detected via contact force sensors. Applicable to logistics, service robots, and autonomous platforms, this system enables remote operation of multiple robots, reduces the need for human intervention, and improves overall task quality and efficiency in remote environments.
This invention was developed with support from the Ministry of Knowledge Economy for the development of remote operation service engines and force-feedback remote-controlled robot system technologies for remote tasks.
This technology is an automated inspection mechanism that utilizes a body traveling between rails equipped with multiple non-contact optical sensors to measure rail gauge (width), surface condition, notches, edge damage, and cracks at connection points, with a control unit that analyzes this data to provide maintenance insights.
Conventional rail inspection is performed manually by workers, which is time-consuming and labor-intensive, while also being prone to subjective judgment, missed inspections, and safety risks in the work environment.
This technology implements an automated system that precisely measures the condition of each rail section using first through fifth sensors positioned on both sides and the top guide of the body. It utilizes cameras for autonomous navigation and a control unit for data analysis to identify and report damage locations to operators. Applicable to logistics transport, service robots, and autonomous platforms, it enhances the efficiency and accuracy of rail inspections, reduces the risk of accidents and human error, and minimizes the need for manual labor and associated costs.
This invention was developed with support from the Ministry of Education, Science and Technology for the development of convergence technology for new and renewable energy intelligent robots.
This technology combines direct operator teaching with automated robot control assistance for peg-in-hole assembly processes involving multi-peg components. It optimizes robot playback performance by automatically or selectively removing teaching data from unnecessary segments where no robot movement occurs, using linear and angular velocity analysis.
Conventional position-based direct teaching is difficult to implement for complex assembly tasks involving contact, such as inserting multiple pegs. Furthermore, inefficient stationary data generated during manual teaching by operators often leads to unnecessary delays in robot playback time.
This technology establishes a teaching procedure for inserting multiple pegs of varying lengths in stages (primary and secondary). It applies a data editing algorithm that analyzes the linear and angular velocity components based on the robot's tool coordinate system to identify stationary segments, then automatically or selectively removes that data via a user interface. Applicable to robot gripping, precision measurement, and automated equipment, it improves overall assembly efficiency and reduces robot playback time.
This technology features a multi-jointed mobile robot that connects its body and arms using multiple link members, with curved sections and elastic damping structures formed on the underside of each, allowing it to adaptively navigate and traverse stair steps.
Conventional wheeled robots are efficient for travel on flat surfaces with uniform height, but they face structural limitations when effectively navigating uneven terrain such as stairs.
This technology incorporates repeating curved sections along the bottom of the housing and arms, utilizes elastic damping members, and controls relative positioning via rod-shaped connecting members to vary the contact surface. It can be applied to indoor delivery robots and building inspection robots, enabling smooth and stable movement even in environments with stairs and thresholds.
This technology features a vibratory robot that forms a tubular structure by connecting multiple vibration modules in a ring shape. Each module contains an electromagnetic vibration unit composed of a coil, a magnet, and an elastic member, allowing for the control of vibration amplitude, frequency, and phase to achieve both flight and driving locomotion.
Existing flying robots are significantly affected by air currents and have limited low-altitude flight capabilities, while ground-based robots face movement constraints due to the physical limitations of wheels or tracks, which restrict their range depending on terrain conditions.
This technology changes its structure between flight and driving modes by varying the angles of the top and bottom of the modules. By applying individual AC power to each module, it controls thrust and direction through asymmetric amplitude and phase modulation. Applicable to indoor exploration and disaster site reconnaissance, it introduces a new mode of mobility that allows a single robot to transition between flying and driving.
