Pub Date : 2023-10-31DOI: 10.5302/j.icros.2023.23.0101
Fikih Muhamad, Jung-Su Kim
Robotics research has achieved rapid development in the field of quadruped robots. These robots can traverse uneven terrains better than similar sized wheeled robots. However, challenges related to their affordability, complex mechanical design, and sensor placement remain. Regarding affordability, existing quadruped robot platforms utilize custom-made actuators, increasing their cost and exclusivity. Further, their complex mechanical and electrical systems pose challenges in their construction and maintenance. Many existing platforms also lack sufficient space for sensor placement, this adversely affects their performance when navigating uneven terrains that require multiple sensors. To overcome these challenges, this study proposes Dynabot, a small-sized quadruped platform that uses Dynamixel servos and frames on each foot. The main body of the Dynabot is composed of aluminum frames and acrylics. This design aims to improve cost efficiency, ease the assembling and disassembling process, and provide flexibility for sensor placement. To validate the Dynabot’s performance, its abilities to utilize an inverse kinematic planner and a gait planner in its locomotion, and to traverse stairs without falling are demonstrated via both simulations and the real-world experiments. The Unified robot description format of the Dynabot can be accessed at https://url.kr/aq6obp.
{"title":"Dynabot: Modular Quadruped Platform With Dynamixel","authors":"Fikih Muhamad, Jung-Su Kim","doi":"10.5302/j.icros.2023.23.0101","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0101","url":null,"abstract":"Robotics research has achieved rapid development in the field of quadruped robots. These robots can traverse uneven terrains better than similar sized wheeled robots. However, challenges related to their affordability, complex mechanical design, and sensor placement remain. Regarding affordability, existing quadruped robot platforms utilize custom-made actuators, increasing their cost and exclusivity. Further, their complex mechanical and electrical systems pose challenges in their construction and maintenance. Many existing platforms also lack sufficient space for sensor placement, this adversely affects their performance when navigating uneven terrains that require multiple sensors. To overcome these challenges, this study proposes Dynabot, a small-sized quadruped platform that uses Dynamixel servos and frames on each foot. The main body of the Dynabot is composed of aluminum frames and acrylics. This design aims to improve cost efficiency, ease the assembling and disassembling process, and provide flexibility for sensor placement. To validate the Dynabot’s performance, its abilities to utilize an inverse kinematic planner and a gait planner in its locomotion, and to traverse stairs without falling are demonstrated via both simulations and the real-world experiments. The Unified robot description format of the Dynabot can be accessed at https://url.kr/aq6obp.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"15 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135769519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.5302/j.icros.2023.23.0094
Su-Young Choi, Young-Yeol Choo
The Internet of Things (IoT) encompasses all Internet communication technologies. In particular, wireless sensor networks(WSNs) play an important role in various IoT applications, such as home network, smart factory, and smart city. The Internet Engineering Task Force (IETF), an internet standardization organization, had proposed a lightweight protocol called constrained application protocol (CoAP) for the Internet connectivity of low-performance devices such as WSNs. Because the CoAP employed the user datagram protocol, and a simple congestion control mechanism based on binary exponential backoff, it showed significant delay in lossy network conditions. To overcome this, the IETF Constrained RESTful Environments (CoRE) working group proposed the CoAP Simple Congestion Control/Advanced (CoCoA) algorithm. However, the CoCoA algorithm suffered from high computational overhead for RTO calculation at every transmission of packets, leading to increased energy consumption by the sensor nodes. Moreover, the use of a fixed weighting parameter in the calculation of round-trip time (RTT) resulted in a slow response to the rapidly changing network environment.BR This study proposes an algorithm to efficiently assess the network conditions by measuring the RTT and the number of re-transmissions over a certain period or number of communication rounds. Statistical techniques were applied to determine the network’s loss rate; further, based on the identified loss rate, different weighting factors (α) were applied to calculate the predicted RTT values. Proposed algorithm was designed to reduce the computational overhead for RTO calculations and to be adaptive to the network conditions exhibiting significant RTT variations. The algorithm was compared with CoCoA and the existing smoothed round trip time (SRTT) algorithm applied in the traditional Internet using the Cooja simulator. The simulations were performed under wireless environments with loss rates of 5%, 10%, and 15%, respectively. The performance was measured by conducting 1,000 exchanges of CON-ACK packet pairs until successful communication was achieved. In each loss rates, the performance of the proposed algorithm was superior to those of the CoCoA and the SRTT algorithms in terms of total communication time.
{"title":"Design of Adaptive RTO Algorithm for Efficient Congestion Control in CoAP-based Wireless Lossy Environments","authors":"Su-Young Choi, Young-Yeol Choo","doi":"10.5302/j.icros.2023.23.0094","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0094","url":null,"abstract":"The Internet of Things (IoT) encompasses all Internet communication technologies. In particular, wireless sensor networks(WSNs) play an important role in various IoT applications, such as home network, smart factory, and smart city. The Internet Engineering Task Force (IETF), an internet standardization organization, had proposed a lightweight protocol called constrained application protocol (CoAP) for the Internet connectivity of low-performance devices such as WSNs. Because the CoAP employed the user datagram protocol, and a simple congestion control mechanism based on binary exponential backoff, it showed significant delay in lossy network conditions. To overcome this, the IETF Constrained RESTful Environments (CoRE) working group proposed the CoAP Simple Congestion Control/Advanced (CoCoA) algorithm. However, the CoCoA algorithm suffered from high computational overhead for RTO calculation at every transmission of packets, leading to increased energy consumption by the sensor nodes. Moreover, the use of a fixed weighting parameter in the calculation of round-trip time (RTT) resulted in a slow response to the rapidly changing network environment.BR This study proposes an algorithm to efficiently assess the network conditions by measuring the RTT and the number of re-transmissions over a certain period or number of communication rounds. Statistical techniques were applied to determine the network’s loss rate; further, based on the identified loss rate, different weighting factors (α) were applied to calculate the predicted RTT values. Proposed algorithm was designed to reduce the computational overhead for RTO calculations and to be adaptive to the network conditions exhibiting significant RTT variations. The algorithm was compared with CoCoA and the existing smoothed round trip time (SRTT) algorithm applied in the traditional Internet using the Cooja simulator. The simulations were performed under wireless environments with loss rates of 5%, 10%, and 15%, respectively. The performance was measured by conducting 1,000 exchanges of CON-ACK packet pairs until successful communication was achieved. In each loss rates, the performance of the proposed algorithm was superior to those of the CoCoA and the SRTT algorithms in terms of total communication time.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"15 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135769349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0090
Sungryul Lee
This paper addresses the adaptive-output-feedback consensus of linear multi-agent systems under a directed graph. The proposed protocol employs a local state observer to estimate the true state of each agent. The coupling weight of each agent is adjusted in a piecewise constant manner using a switching logic that uses only estimated states received from neighboring agents. The proposed consensus protocol is completely decentralized, as it uses only local information from neighboring agents. Moreover, the proposed design method is advantageous because it has a simpler structure and requires less computational burden than the existing protocols related to adaptive-output-feedback consensus.
{"title":"Adaptive Output Feedback Consensus of Linear Multi-agent Systems Using Switching Logic","authors":"Sungryul Lee","doi":"10.5302/j.icros.2023.23.0090","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0090","url":null,"abstract":"This paper addresses the adaptive-output-feedback consensus of linear multi-agent systems under a directed graph. The proposed protocol employs a local state observer to estimate the true state of each agent. The coupling weight of each agent is adjusted in a piecewise constant manner using a switching logic that uses only estimated states received from neighboring agents. The proposed consensus protocol is completely decentralized, as it uses only local information from neighboring agents. Moreover, the proposed design method is advantageous because it has a simpler structure and requires less computational burden than the existing protocols related to adaptive-output-feedback consensus.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0100
Jongik Jeong, Doyoon Ju, Yusuke Fujiyama, Young-Sam Lee
This study investigates the transition control problem for a double inverted pendulum system, which has one stable and three unstable equilibrium points. We propose a method for implementing transition control using a lab-built double inverted pendulum and extend swing-up control to achieve this. The proposed method uses a two-degree-of-freedom control structure that combines feedforward and feedback controls. To obtain the feedforward trajectories offline, we construct an optimal control problem with two-point boundary values that has constraints on the dynamic equations, boundary values at the equilibrium points, and input and output constraints. We use energy as the cost of the optimal control problem and employ a direct collocation method to transform the continuous-time optimal control problem with constraints into a nonlinear optimization problem. During real-time control, we use a time-varying LQ controller as a feedback controller to compensate for the uncertainty of feedforward control and accurately follow the feedforward trajectories. We implement the proposed transition control based on high-level thinking using the lab-built light-weight rapid control prototyping (LW-RCP) system to shorten the design time and provide useful information in the design and experiment processes. Finally, we perform an actual transition control experiment and validate the performance of the proposed method using the experimental results.
{"title":"Transition Control of a Double Inverted Pendulum Using an LW-RCP","authors":"Jongik Jeong, Doyoon Ju, Yusuke Fujiyama, Young-Sam Lee","doi":"10.5302/j.icros.2023.23.0100","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0100","url":null,"abstract":"This study investigates the transition control problem for a double inverted pendulum system, which has one stable and three unstable equilibrium points. We propose a method for implementing transition control using a lab-built double inverted pendulum and extend swing-up control to achieve this. The proposed method uses a two-degree-of-freedom control structure that combines feedforward and feedback controls. To obtain the feedforward trajectories offline, we construct an optimal control problem with two-point boundary values that has constraints on the dynamic equations, boundary values at the equilibrium points, and input and output constraints. We use energy as the cost of the optimal control problem and employ a direct collocation method to transform the continuous-time optimal control problem with constraints into a nonlinear optimization problem. During real-time control, we use a time-varying LQ controller as a feedback controller to compensate for the uncertainty of feedforward control and accurately follow the feedforward trajectories. We implement the proposed transition control based on high-level thinking using the lab-built light-weight rapid control prototyping (LW-RCP) system to shorten the design time and provide useful information in the design and experiment processes. Finally, we perform an actual transition control experiment and validate the performance of the proposed method using the experimental results.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136277037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0096
Soojin Lee, Jiheon Kang
This paper introduces a lightweight deep learning model for human-hand-gesture recognition, leveraging point cloud data acquired from a mmWave radar. The proposed 2D projection method can be applied for the preprocessing of input data for lightweight deep learning models by effectively preserving the spatial and coordinate information of each point within the 3D voxel point cloud. In addition, we proposed a 2D-CNN-TCN deep learning model that significantly reduces the number of learnable parameters while maintaining or improving the accuracy of hand-gesture recognition. The mmWave radar sensor module used in this study was IWR6843AoPEVM from Texas Instruments, and a comprehensive dataset consisting of nine distinct hand gestures was collected, with each gesture captured over a duration of 20–25 min, resulting in a total collection time of 190 min. The proposed model was trained and evaluated on a general-purpose PC. The proposed 2D-CNN-TCN model was compared to the 3D-CNN-LSTM model to reflect the 3D voxel input and time-series characteristics. The performance evaluation demonstrated that the performance of the proposed model was 1.3% enhanced with respect to the 3D-CNN-LSTM model, resulting in a recognition accuracy of 95.06% for the proposed model. Moreover, the proposed model achieved a 5.5% reduction in the number of model parameters with respect to the 3D-CNN-LSTM model. Furthermore, the lightweight deep learning model was successfully deployed as an Android application, and the usability of the model was verified through real-time hand-gesture recognition.
{"title":"Lightweight Deep Learning Model for Hand Gesture Recognition Based on ㎜Wave Radar Point Cloud","authors":"Soojin Lee, Jiheon Kang","doi":"10.5302/j.icros.2023.23.0096","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0096","url":null,"abstract":"This paper introduces a lightweight deep learning model for human-hand-gesture recognition, leveraging point cloud data acquired from a mmWave radar. The proposed 2D projection method can be applied for the preprocessing of input data for lightweight deep learning models by effectively preserving the spatial and coordinate information of each point within the 3D voxel point cloud. In addition, we proposed a 2D-CNN-TCN deep learning model that significantly reduces the number of learnable parameters while maintaining or improving the accuracy of hand-gesture recognition. The mmWave radar sensor module used in this study was IWR6843AoPEVM from Texas Instruments, and a comprehensive dataset consisting of nine distinct hand gestures was collected, with each gesture captured over a duration of 20–25 min, resulting in a total collection time of 190 min. The proposed model was trained and evaluated on a general-purpose PC. The proposed 2D-CNN-TCN model was compared to the 3D-CNN-LSTM model to reflect the 3D voxel input and time-series characteristics. The performance evaluation demonstrated that the performance of the proposed model was 1.3% enhanced with respect to the 3D-CNN-LSTM model, resulting in a recognition accuracy of 95.06% for the proposed model. Moreover, the proposed model achieved a 5.5% reduction in the number of model parameters with respect to the 3D-CNN-LSTM model. Furthermore, the lightweight deep learning model was successfully deployed as an Android application, and the usability of the model was verified through real-time hand-gesture recognition.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0077
Songeun Park, Jungwook Suh
Ackermann steering can reduce the turning radius of a vehicle to a limited extent, and individual steering for mobile robots increases cost owing to the need for more actuators. Therefore, in this paper, we propose a novel front-back-symmetric-steering mechanism that allows four-wheel steering using only two actuators. A robot prototype is fabricated to verify the basic performance of this design. The proposed steering system has no restriction on the change of the steering angle; therefore, the robot can rotate in place without lateral slip of the wheels. In addition, the four-wheel-drive function combined with the steering mechanism facilitates smooth driving even on somewhat uneven road surfaces without requiring a suspension system. As a result, the proposed steering mechanism is expected to apply to various mobile robots owing to its simplicity and the ability to achieve excellent rotation characteristics.
{"title":"Design of Front-back Symmetric Four-wheel-steering Mobile Robot","authors":"Songeun Park, Jungwook Suh","doi":"10.5302/j.icros.2023.23.0077","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0077","url":null,"abstract":"Ackermann steering can reduce the turning radius of a vehicle to a limited extent, and individual steering for mobile robots increases cost owing to the need for more actuators. Therefore, in this paper, we propose a novel front-back-symmetric-steering mechanism that allows four-wheel steering using only two actuators. A robot prototype is fabricated to verify the basic performance of this design. The proposed steering system has no restriction on the change of the steering angle; therefore, the robot can rotate in place without lateral slip of the wheels. In addition, the four-wheel-drive function combined with the steering mechanism facilitates smooth driving even on somewhat uneven road surfaces without requiring a suspension system. As a result, the proposed steering mechanism is expected to apply to various mobile robots owing to its simplicity and the ability to achieve excellent rotation characteristics.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0081
Gwonsoo Lee, Kihwan Choi, Phil-Yeob Lee, Ho-Sung Kim, Hansol Lee, Hyungjoo Kang, Jihong Lee
This paper presents an improved approach for in-motion alignment based on position estimation to accurately determine the initial heading-angle of an autonomous underwater vehicle. The existing method for in-motion alignment is highly sensitive to errors from GPS reception and the localization algorithm, particularly in the vicinity of the starting point. Consequently, compensation values for the heading-angle obtained in the vicinity of the starting point are unreliable. To address this issue, this study analyzes the variance of the heading-angle compensation during the early stage of the alignment process, aiming to assess the reliability of the compensation value. By using variance as a criterion, the algorithm determines whether to continue the execution of the early stage in the alignment process. If the variance falls below a certain threshold, the algorithm calculates the correction value of the final heading-angle based on each correction value. The proposed algorithm is validated through practical experiments using sensor data collected from real-sea environments. The experimental results demonstrate an average improvement of 50.48% in localization performance with respect to the existing algorithm. Therefore, the proposed algorithm enhances the performance of the in-motion alignment algorithm.
{"title":"Performance Enhancement Technique for Position-based Alignment Algorithm in AUV’s Navigation","authors":"Gwonsoo Lee, Kihwan Choi, Phil-Yeob Lee, Ho-Sung Kim, Hansol Lee, Hyungjoo Kang, Jihong Lee","doi":"10.5302/j.icros.2023.23.0081","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0081","url":null,"abstract":"This paper presents an improved approach for in-motion alignment based on position estimation to accurately determine the initial heading-angle of an autonomous underwater vehicle. The existing method for in-motion alignment is highly sensitive to errors from GPS reception and the localization algorithm, particularly in the vicinity of the starting point. Consequently, compensation values for the heading-angle obtained in the vicinity of the starting point are unreliable. To address this issue, this study analyzes the variance of the heading-angle compensation during the early stage of the alignment process, aiming to assess the reliability of the compensation value. By using variance as a criterion, the algorithm determines whether to continue the execution of the early stage in the alignment process. If the variance falls below a certain threshold, the algorithm calculates the correction value of the final heading-angle based on each correction value. The proposed algorithm is validated through practical experiments using sensor data collected from real-sea environments. The experimental results demonstrate an average improvement of 50.48% in localization performance with respect to the existing algorithm. Therefore, the proposed algorithm enhances the performance of the in-motion alignment algorithm.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0086
Hyun-Jin Chun, Incheol Kim
Video instance segmentation (VIS) is a vision task that involves simultaneously detecting, classifying, segmenting, and tracking object instances in videos. In this study, we introduce dynamic anchor box and deformable attention for VIS (DAB-D-VIS), a novel transformer-based model for online VIS. To enhance the multilayer transformer-based instance decoding for each video frame, our proposed model uses deformable attention mechanisms that focus on a small set of key sampling points. Additionally, dynamic anchor boxes are employed to explicitly represent the region of candidate instances. These two methods have already been proven to be effective for transformer-based object detection from images. Furthermore, to address the constraints of online VIS, our model incorporates a robust inter-frame instance association method. This method leverages both similarity in the contrastive embedding space and positional difference in the images between two instances. Extensive experiments conducted on the YouTube-VIS benchmark dataset validate the effectiveness of our proposed DAB-D-VIS model.
{"title":"Dynamic Anchor Box-based Instance Decoding and Position-aware Instance Association for Online Video Instance Segmentation","authors":"Hyun-Jin Chun, Incheol Kim","doi":"10.5302/j.icros.2023.23.0086","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0086","url":null,"abstract":"Video instance segmentation (VIS) is a vision task that involves simultaneously detecting, classifying, segmenting, and tracking object instances in videos. In this study, we introduce dynamic anchor box and deformable attention for VIS (DAB-D-VIS), a novel transformer-based model for online VIS. To enhance the multilayer transformer-based instance decoding for each video frame, our proposed model uses deformable attention mechanisms that focus on a small set of key sampling points. Additionally, dynamic anchor boxes are employed to explicitly represent the region of candidate instances. These two methods have already been proven to be effective for transformer-based object detection from images. Furthermore, to address the constraints of online VIS, our model incorporates a robust inter-frame instance association method. This method leverages both similarity in the contrastive embedding space and positional difference in the images between two instances. Extensive experiments conducted on the YouTube-VIS benchmark dataset validate the effectiveness of our proposed DAB-D-VIS model.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0088
Seungbum Lim, Hyein Jung, Jungwook Suh
The elasticity of human skin and the complexity of human joints can lead to misalignment between an exoskeleton robot and the human body. This misalignment increases physical human-robot interaction forces, resulting in discomfort and pain for the wearer. Consequently, considering these interaction forces is crucial for ensuring the safety of wearing an exoskeleton. In this study, we propose a novel method to statically predict physical human-robot interaction forces and evaluate the safety of using exoskeleton robots. To validate the interaction model, experiments are conducted using a sensor-equipped upper limb dummy and an exoskeleton robot. The results confirm the effectiveness of the proposed method, allowing for the quantitative assessment of the safety of using exoskeleton robots without the need for manufacturing actual prototypes.
{"title":"Static Modeling and Experimental Verification for Safety Evaluation of Human-robot Interaction in Exoskeleton Robots","authors":"Seungbum Lim, Hyein Jung, Jungwook Suh","doi":"10.5302/j.icros.2023.23.0088","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0088","url":null,"abstract":"The elasticity of human skin and the complexity of human joints can lead to misalignment between an exoskeleton robot and the human body. This misalignment increases physical human-robot interaction forces, resulting in discomfort and pain for the wearer. Consequently, considering these interaction forces is crucial for ensuring the safety of wearing an exoskeleton. In this study, we propose a novel method to statically predict physical human-robot interaction forces and evaluate the safety of using exoskeleton robots. To validate the interaction model, experiments are conducted using a sensor-equipped upper limb dummy and an exoskeleton robot. The results confirm the effectiveness of the proposed method, allowing for the quantitative assessment of the safety of using exoskeleton robots without the need for manufacturing actual prototypes.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5302/j.icros.2023.23.0083
Hyobin Suk, Mooncheol Won
We developed a methodology to achieve position estimation, path planning and control for autonomous docking systems of autonomous mobile robots (AMRs). For autonomous docking, the relative position between the AMR and the docking station must be accurately estimated. The relative position determined using a camera and lidar sensors is inaccurate, and the position update rate is insufficient. To solve this problem, we propose a Kalman filter that uses an inertial measurement unit and information from a wheel encoder sensor in combination. The position estimated by the Kalman filter has a smaller root mean square error and variance than those obtained from the camera and lidar sensors, and the position is updated every 25 ms. The control system for path planning and docking was implemented in the Robot Operating System, and the algorithm was verified through Gazebo simulation. Finally, the developed algorithm was verified in real environments. The experimental results yielded a position error of less than 1 cm and an angle error of less than 1°.
{"title":"Docking Control Algorithm for Autonomous Mobile Robot Through Sensor Fusion","authors":"Hyobin Suk, Mooncheol Won","doi":"10.5302/j.icros.2023.23.0083","DOIUrl":"https://doi.org/10.5302/j.icros.2023.23.0083","url":null,"abstract":"We developed a methodology to achieve position estimation, path planning and control for autonomous docking systems of autonomous mobile robots (AMRs). For autonomous docking, the relative position between the AMR and the docking station must be accurately estimated. The relative position determined using a camera and lidar sensors is inaccurate, and the position update rate is insufficient. To solve this problem, we propose a Kalman filter that uses an inertial measurement unit and information from a wheel encoder sensor in combination. The position estimated by the Kalman filter has a smaller root mean square error and variance than those obtained from the camera and lidar sensors, and the position is updated every 25 ms. The control system for path planning and docking was implemented in the Robot Operating System, and the algorithm was verified through Gazebo simulation. Finally, the developed algorithm was verified in real environments. The experimental results yielded a position error of less than 1 cm and an angle error of less than 1°.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136276819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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