Journal of the Korean Society for Precision Engineering

Development of an Actuator and Controller for Robotic Joints Integrating a Frameless BLDC Motor and a Stepped Planetary Gear Reducer: Sangsin Park; J. Korean Soc. Precis. Eng. 2026;43(2):183-188.
Published online February 1, 2026; DOI: https://doi.org/10.7736/JKSPE.025.105

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This paper details the design and development of a robotic joint actuator that combines a frameless BLDC motor with a two-stage stepped planetary gear reducer, as well as a custom-built controller for precise position control. The rotor is physically coupled to a hollow sun gear shaft to facilitate internal cable routing, and the actuator features a high-resolution absolute encoder utilizing the BiSS-C protocol. The controller includes a 3-phase H-bridge driver, differential signal conversion for encoder communication, and a CAN interface for host communication. Position control is achieved through a PID loop operating at 1 kHz. A prototype actuator and controller have been fabricated, and step response tests were conducted. Experimental results indicate stable and accurate tracking of position commands, with a short settling time of 0.04773 seconds. These findings confirm the effectiveness of the integrated actuator system for robotic joint applications. Future work will focus on optimizing internal cable space and implementing sensorless control algorithms.

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Development of a Adjustable fastening Mechanism for Wearable Robots Utilizing the Poisson's Ratio Properties of Braided Sleeves: Yong-Sin Seo, Jae-Young Lee, Cheol Hoon Park, Sung-Hyuk Song; J. Korean Soc. Precis. Eng. 2026;43(2):151-157.
Published online February 1, 2026; DOI: https://doi.org/10.7736/JKSPE.025.092

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This study introduces a novel adjustable fastening mechanism for wearable robots, aimed at alleviating user discomfort associated with traditional fixed attachment methods. By utilizing the unique scissoring effect of braided sleeves, we demonstrated that axial manipulation can effectively translate into radial size control, allowing for precise regulation of fastening force. To address the size limitations of commercial braided sleeves, we developed a large-area fastening structure by combining multiple braided sleeve sheets. Additionally, we incorporated a wire tendon system to enable active operation in both Daily Mode (fastening-release) and Exercise Mode (fastening-tightening). Experimental results on an anthropomorphic model revealed that this adjustable fastening structure offers variable fastening forces, achieving a 4.8-fold difference between the exercise and daily modes. This research presents a new approach by leveraging the Poisson's ratio properties of braided sleeves for dynamic fastening, tackling fabrication challenges for large-area structures, and improving user comfort and compliance in wearable robot applications

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A Study on Improving Multi-agent Path Finding in Congested Environments Using Agent Merging and Splitting: SeoHyun Yoo, SeongTaek Im, HyoJae Kang, ChanHee Jeong, DaeHee Han, Min-Sung Kang; J. Korean Soc. Precis. Eng. 2026;43(2):123-131.
Published online February 1, 2026; DOI: https://doi.org/10.7736/JKSPE.025.044

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The rising demand for robots in warehouses has highlighted the need for efficient multi-robot algorithms. In response, researchers have focused on Multi-Agent Path Finding (MAPF), which enables multiple agents to calculate conflict-free paths to their individual goals. However, the computation time of conflict-based MAPF algorithms significantly increases as the number of conflicts rises, a common challenge in warehouse environments with narrow passages or corridors. To tackle this issue, this study introduces a new type of conflict called “Overlap Conflict.” Overlap Conflicts occur when an agent stops, causing chain conflicts among subsequent agents traveling in the same direction. When an Overlap Conflict arises, the affected agents are dynamically merged into a single group, shifting the conflicts from an individual level to a group level. If the merged agents find themselves with unreachable goals, they are split back into individual agents to continue calculating paths to their respective destinations. This approach effectively reduces computation time in congested environments, particularly in narrow corridors where alternative routes exist.

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Estimation of Kinematic Parameters of a 6-Axis Serial Robot through a Circular Test Using a Double Ball-Bar: Heung Ki Jeon, Sung Hwan Kweon, Kwang Il Lee, Seung Han Yang; J. Korean Soc. Precis. Eng. 2026;43(1):69-77.
Published online January 1, 2026; DOI: https://doi.org/10.7736/JKSPE.025.079

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This study introduces a straightforward and cost-effective method to enhance the positional accuracy of a 6-axis serial robot using a double ball-bar (DBB). Kinematic errors, a primary source of inaccuracies in offline programming, are estimated and calibrated through circular tests. The kinematics of the robot are modeled using the Denavit-Hartenberg (D-H) convention, and a mathematical relationship between radial deviation and kinematic errors is established. To avoid singularities, identifiable parameters are selected using singular value decomposition. The method involves three steps: measuring the tool center point (TCP) with the DBB, estimating key kinematic parameters, and verifying the calibration results. Redundant or less significant parameters are excluded to concentrate on the most impactful ones. During the process, the robot is commanded to trace a circular path while radial deviations are recorded. This data is then utilized to estimate and adjust the kinematic model. After recalculating and executing the circular path with the calibrated model, a notable reduction in deviation is achieved. This proposed approach requires no additional equipment and provides a quick, affordable solution for improving the accuracy of industrial robots while lowering maintenance costs.

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Ceiling Hazardous Object Inspection Robot for Counter-terrorism Security Check: Sangwoong Lee, Daegwon Koh, Meungsuk Lee, Hyeongseok Song, Juhyun Pyo, Jinho Suh, Murim Kim; J. Korean Soc. Precis. Eng. 2026;43(1):37-46.
Published online January 1, 2026; DOI: https://doi.org/10.7736/JKSPE.025.047

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Ceiling inspections present challenges due to limited accessibility and structural constraints. To ease the burden on security personnel, who would otherwise need to manually disassemble, inspect, and restore ceiling components, this study proposes a robotic system for detecting hazardous objects within ceiling environments. The proposed system features several key innovations: a hollow-structured track mechanism designed to reduce vibrations from jolting while traversing structural beams and to improve localization accuracy. We optimized the robot’s mass distribution and required drive torque through dynamic simulations to ensure stable mobility in confined ceiling spaces. For effective hazardous object detection, we developed a YOLOv8-Seg-based background learning algorithm that suppresses ceiling-structure patterns, allowing for the identification of unknown objects without prior class-specific training. Additionally, we introduced a frame-based filtering algorithm to enhance detection reliability by reducing false positives caused by motion blur during movement. The system's effectiveness was validated through experiments conducted in a ceiling-structured testbed, demonstrating its capability for accurate hazardous object detection under realistic operating conditions.

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Dynamic Characteristic-based Driving Performance Analysis of a Semi-active Suspension Wheel Module for Small Mobile Robots: Seoyeon Park, Sungjae Kim, Juhyun Pyo, Murim Kim, Jin-Ho Suh; J. Korean Soc. Precis. Eng. 2025;42(11):919-926.
Published online November 1, 2025; DOI: https://doi.org/10.7736/JKSPE.025.069

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This study details the development of a semi-active suspension wheel module for small mobile robots and assesses its dynamic characteristics under various driving conditions through simulation. The wheel module features a low-degree-of-freedom mechanical design and includes a semi-active damper to improve adaptability to different environments. To validate the simulation model, a prototype robot equipped with the wheel module was created, and obstacle-crossing experiments were conducted to measure vertical acceleration responses. The model was then refined based on these experimental results. By employing design of experiments and optimization techniques, the effective range of damping coefficients was estimated. Additionally, simulations were carried out at different speeds, payloads, and obstacle heights to identify optimal damping values and examine their trends. The results indicate that the proposed module significantly enhances driving stability and can serve as a foundation for future control strategies in robotic mobility systems.

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Design and Control of Master Device with Force Feedback for Teleoperated ERCP Guidewire Insertion: Woocheol Shin, SeongHyeon Won, YongJung Lee, Daehie Hong; J. Korean Soc. Precis. Eng. 2025;42(9):723-733.
Published online September 1, 2025; DOI: https://doi.org/10.7736/JKSPE.024.133

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ERCP (Endoscopic Retrograde Cholangiopancreatography) is a common procedure used to diagnose and treat biliary and pancreatic diseases. However, the repeated exposure to X-ray radiation during these procedures poses health risks to surgeons. Teleoperation systems can help reduce this exposure, but they face challenges such as the lack of force feedback and differences between the master device's mechanisms and the movements of surgical tools, which can diminish surgical precision. This study aimed to develop a master device with force feedback specifically for teleoperated ERCP guidewire insertion, drawing inspiration from the natural hand movements of surgeons. The device includes a ring-shaped translation control handle and a rotation control handle, both designed to allow unlimited movement, thereby intuitively replicating the operation of the guidewire. A force feedback system was incorporated to enable collision detection and prevent potential injuries during procedures. Experimental results showed that the proposed system enhances control precision, reduces handling inertia, and provides effective force feedback. These advancements ensure safer and more accurate guidewire manipulation, addressing key limitations of existing teleoperation systems. Ultimately, this device not only minimizes radiation exposure for surgeons but also facilitates intuitive and precise teleoperated ERCP procedures.

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Verification of Remote Center Motion Performance of a Surgical Assistant Robot without Holding Trocars: TaeHoon Kim, Minhyo Kim, Youqiang Zhang, Hyunseok Choi, Hyeon Kim, JunSeok Park, Sangrok Jin; J. Korean Soc. Precis. Eng. 2025;42(8):629-636.
Published online August 1, 2025; DOI: https://doi.org/10.7736/JKSPE.025.054

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In laparoscopic surgeries, robotic systems commonly use trocar fixation to achieve remote center motion (RCM). However, this fixation occupies the surgeon's operational space and limits surgical flexibility. It is essential to ensure adequate workspace while maintaining RCM to enhance procedural efficiency and safety. This paper introduces a novel approach to preserve RCM without relying on trocar fixation. The proposed method integrates a six-degree-of-freedom robotic arm with a dual end-effector system, employing tool coordinate storage and remote center point definition to achieve precise four- degree-of-freedom RCM motion control. To validate this method, an experimental setup with an optical tracking system was utilized to measure and calibrate the remote center position. The results indicate that the robot maintained RCM with mean positional errors of 0.672, 0.318, and 0.704 mm along the x, y, and z axes, respectively, yielding a three-dimensional mean error of 1.136 mm. These findings demonstrate the effectiveness of the method in maintaining RCM while maximizing surgical workspace and operational flexibility.

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Development of Robotic Fiber Positioner and Path Planning Algorithm for Multi-object Spectroscopy: Hyunho Lim, Jae-Woo Kim, Ho Seong Hwang, Sungwook Hong, Jong Chul Lee, Young-Man Choi; J. Korean Soc. Precis. Eng. 2025;42(1):79-88.
Published online January 1, 2025; DOI: https://doi.org/10.7736/JKSPE.024.120

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A robotic focal plane system using robotic fiber positioners enables multi-object spectroscopy for hundreds to thousands of galaxies by utilizing a dense array of positioners that are closely packed at the focal plane of a telescope. While this dense arrangement increases the number of observations, it also introduces the potential for collisions between adjacent positioners. A fiber positioner is designed similarly to a SCARA robot. It is driven by two series of BLDC motors. Each positioner is manufactured with an outer diameter of 16 mm. It operates within an annular workspace with an outer diameter of 33.6 mm and an inner diameter of 12.8 mm. As these positioners are arranged with a spacing of 16.8 mm, target assignment and motion planning are critical to avoid collisions caused by overlapping workspaces. To address this, we proposed an optimized step choice algorithm using a motion planning method based on optimization with the sequential quadratic programming algorithm. Simulation results demonstrated that paths for all positioners within a tile were successfully generated with a success rate of up to 93.75% across 80 tiles.

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Development of an Autonomous Stair Driving System based on an Object Detection Algorithm through Analysis of Stair Traversal Conditions of a Tracked Robot: Min Gi Song, Sung-Jae Kim, Jin-Ho Suh; J. Korean Soc. Precis. Eng. 2025;42(1):27-38.
Published online January 1, 2025; DOI: https://doi.org/10.7736/JKSPE.024.097

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In this paper, we propose an autonomous stair-driving system for the stable traversal of stairs by a tracked mobile robot operating in indoor disaster environments. Before developing the system, we conduct dynamic simulations to analyze the requirements for the robot to climb stairs. Simulations are performed under various initial conditions, and based on a detailed analysis of the results, we derive the necessary conditions for the robot's ascent. Using these requirements, we design the autonomous stair-driving system, which includes three main components: stair approach, stair alignment, and stair traversal. First, during the approach stage, we present a strategy for recognizing stairs using an object detection algorithm and generating control inputs for the stair approach motion. Next, in the alignment process, we outline an image processing sequence that extracts the edge contour of the stairs and a method for generating control inputs from the combined contour. Finally, in the traversal sequence, we describe the strategy for driving up the stairs. Additionally, we introduce an integrated ROS system to ensure the sequential execution of each strategy. We also verify the effectiveness of the individual strategies and demonstrate the capability of the proposed system through experiments using mock-up stairs and tracked robots.

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Research on Four-wheel Steering-based Mobile Robot Driving Control Strategy to Implement Autonomous Driving Service: Do Hyun Kim, Chang Won Kim; J. Korean Soc. Precis. Eng. 2024;41(12):1009-1015.
Published online December 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.106

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This paper proposes an algorithm to improve path planning and tracking performance for autonomous robots using a Four- Wheel Steering (4WS) system in constrained environments. Traditional Ackermann steering systems face limitations in narrow spaces, which the 4WS system aims to address. By extending the Hybrid A* algorithm to adapt to the unique characteristics of the 4WS system, and integrating it with Model Predictive Control, the study achieves efficient path planning and precise tracking in complex environments. A distinctive aspect of the proposed approach is its adaptive control strategy, dynamically switching between three modes—Normal driving, Pivot, and Parallel movement—based on the vehicle's motion state, thus enhancing both flexibility and efficiency. The algorithm's performance was validated through MATLAB simulations in a logistics warehouse setting, showing high path tracking accuracy in confined spaces. The study effectively demonstrates the feasibility of the proposed method in a simulated environment.

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Development of a Statically Balanced Lifting Device for Repetitively Transporting Construction Materials: Byungseo Kwak, Seungbum Lim, Jungwook Suh; J. Korean Soc. Precis. Eng. 2024;41(12):929-937.
Published online December 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.083

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In the field of construction automation, significant research efforts continue to focus on replacing human labor; however, the varied and dynamic nature of construction sites still requires human intervention. The high task intensity in construction sites, particularly in lifting heavy materials, frequently results in musculoskeletal disorders among workers. To address this issue, this paper proposes a lifting device to replace manual material transportation through an opening between floors. The lift is designed with a gear-constrained double parallelogram mechanism to enable straight vertical movement. Moreover, a crank-rocker mechanism is incorporated to improve efficiency in repetitive tasks, reduce the required driving torque, and simplify control complexity. Additionally, this study introduces a passive gravity compensation mechanism that employs springs and cables, tailored to the lifting process, to enhance payload capacity and stabilize actuation. Through the integration of these mechanisms, the necessary motor capacity and control costs are significantly reduced. The effectiveness of the device is validated by actuation experiments with a fabricated prototype.

Citations

Citations to this article as recorded by

Complete gravity balancing of the general four-bar linkage using linear springs
Chin-Hsing Kuo
Mechanism and Machine Theory.2025; 214: 106140. CrossRef

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Optimized Coverage Path Planning for Efficient Autonomous Operation of a Barn Manure Handling Robot: Goo Jun Ji, Myeong Gyu Lee, Won Gun Kim; J. Korean Soc. Precis. Eng. 2024;41(11):827-840.
Published online November 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.065

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In the field of robotics and automation, path planning holds significant potential for optimizing field operations. These operations must cover the work area comprehensively and efficiently with minimal movement. To achieve these goals, coverage path planning (CPP) utilizing the Boustrophedon method is essential. However, in an experimental environment, CPP often results in missed work areas due to cumulative sensor errors and structural inconsistencies. This paper aimed to improve CPP by employing the Douglas-Peucker algorithm to simplify the work path and minimizing missed areas. Additionally, Edge Zone Path method was used to generate edge paths, enhancing safety of the trajectory. For experimental purposes, data were acquired from an actual barn. The work area was divided using three segmentation algorithms. Among these, the Voronoi Segmentation, which demonstrated superior performance, was used to extract the data. Experimental results indicated that the proposed optimized CPP improved path safety by maintaining a safe distance from obstacles during frequent turns. Additionally, the Coverage Ratio increased the coverage area of the autonomous robot by an average of 17% compared to the original CPP. These findings suggest that the proposed method can generate more efficient and safe work paths.

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A Misalignment Diagnosis System for Wafer Transfer Robot based on Deep Learning and Vibration Signal: Su-bin Hong, Hye-jin Kim, Young-dae Lee, Chanwoo Moon; J. Korean Soc. Precis. Eng. 2024;41(10):807-814.
Published online October 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.075

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In the semiconductor manufacturing industry, efficient operation of wafer transfer robots has a direct impact on productivity and product quality. Ball screw misalignment anomalies are a critical factor affecting precision transport of robots. Early diagnosis of these anomalies is essential to maintaining system efficiency. This study proposed a method to effectively diagnose ball screw misalignment anomalies using 1D-CNN and 2D-CNN models. This method mainly uses binary classification to distinguish between normal and abnormal states. Additionally, explainable artificial intelligence (XAI) technology was applied to interpret diagnostic decisions of the two deep learning models, allowing users to convince prediction results of the AI model. This study was based on data collected through acceleration sensors and torque sensors. It compared accuracies of 1D-CNN and 2D-CNN models. It presents a method to explain the model"s predictions through XAI. Experimental results showed that the proposed method could diagnose ball screw misalignment anomalies with high accuracy. This is expected to contribute to the establishment of reliable abnormality diagnosis and preventive maintenance strategies in industrial sites.

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Design and Control of Origami 1T2R Parallel Robot: Hayeon Kim, Hassen Nigatu, Yun Ho Choi, Sang Yong Park, Doik Kim; J. Korean Soc. Precis. Eng. 2024;41(10):783-788.
Published online October 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.015

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Parallel robots exhibit superior precision to serial robots. They operate with reduced power consumption due to load distribution among individual motors. However, symmetrical parallel robots employing a 1T2R structure encounter challenges with parasitic movements at the end-effector, leading to control complexities and application limitations. This study aimed to downsize the robot while ensuring its operational range by employing origami techniques. Addressing the inherent weakness of origami’s stiffness, various methods of material stacking and designed joints with diverse materials and thicknesses were proposed to meet specific angle requirements for each component. The developed control model was validated through simulations and experiments, effectively minimizing parasitic movements by verifying the robot"s motion.