Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324550
Longchuan Li, F. Asano, I. Tokuda
It was clarified that forward locomotion of a seed-like robot on level road surface can be obtained by adding a 2-DOF active wobbling mass. This paper improves the velocity and efficiency of the robot by utilizing 1-DOF wobbling mass with asymmetric wobbling effects. First, we develope the mathematical model and generate the rotation motion of the underactuated robot by applying asymmetric torque. Second, the rotation is efficiently utilized to move forward by introducing asymmetric friction. The robot therefore achieves high-speed locomotion like a seal crawling on the beach. Third, the nonlinear dynamics is analyzed from the synchronization point of view. Finally, we check whether the motor efficiency is increased by our proposed methods. Better than previous studies, the 1-DOF underactuation at the ground-contact point is passively controlled by our proposed methods.
{"title":"High-speed and energy-efficient locomotion of a seed-like underactuated robot on level surface by utilizing asymmetric wobbling effects","authors":"Longchuan Li, F. Asano, I. Tokuda","doi":"10.1109/ROBIO.2017.8324550","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324550","url":null,"abstract":"It was clarified that forward locomotion of a seed-like robot on level road surface can be obtained by adding a 2-DOF active wobbling mass. This paper improves the velocity and efficiency of the robot by utilizing 1-DOF wobbling mass with asymmetric wobbling effects. First, we develope the mathematical model and generate the rotation motion of the underactuated robot by applying asymmetric torque. Second, the rotation is efficiently utilized to move forward by introducing asymmetric friction. The robot therefore achieves high-speed locomotion like a seal crawling on the beach. Third, the nonlinear dynamics is analyzed from the synchronization point of view. Finally, we check whether the motor efficiency is increased by our proposed methods. Better than previous studies, the 1-DOF underactuation at the ground-contact point is passively controlled by our proposed methods.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130040290","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324398
Xiaotian Yang
This paper provides a distributed algorithm for mobile robotic sensors to have a self-deployment in a three-dimensional area to reach the complete blanket coverage. The area with obstacles is arbitrary and unknown. Mobile sensors have limited sensing ranges and communication range. They move in order through a grid pattern to reach a complete coverage. The algorithm sets a reference point. Then the furthest robot moves first to the most distant neighbor in each step without collisions through a grid pattern. Finally, the entire area is covered by a sensor network with the fewest robots and steps. It is proved that the algorithm can converge with probability one. The effectiveness and scalability of the algorithm are shown in simulations of different algorithms in different sizes of areas.
{"title":"A collision-free self-deployment of mobile robotic sensors for three-dimensional distributed blanket coverage control","authors":"Xiaotian Yang","doi":"10.1109/ROBIO.2017.8324398","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324398","url":null,"abstract":"This paper provides a distributed algorithm for mobile robotic sensors to have a self-deployment in a three-dimensional area to reach the complete blanket coverage. The area with obstacles is arbitrary and unknown. Mobile sensors have limited sensing ranges and communication range. They move in order through a grid pattern to reach a complete coverage. The algorithm sets a reference point. Then the furthest robot moves first to the most distant neighbor in each step without collisions through a grid pattern. Finally, the entire area is covered by a sensor network with the fewest robots and steps. It is proved that the algorithm can converge with probability one. The effectiveness and scalability of the algorithm are shown in simulations of different algorithms in different sizes of areas.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128902667","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324742
Roger Datouo, F. B. Motto, B. E. Zobo, A. Melingui, Ismail Bensekrane, R. Merzouki
This paper presents a novel approach of finding energy-efficient trajectories for mobile robots. The approach integrates new cost and heuristic functions into the conventional A∗ algorithm while considering ground conditions and obstacle positions. The resulting planner helps to manage obstacle avoidance and to choose intelligent displacements of the robot. A heuristic function with energy-related criterion is defined in order to generate energy-efficient paths. Splines continuity property is exploited to generate smoothed energy-paths. The optimal velocity profile for minimum travel time is found by solving Sequential Quadratic Problem. A series of simulations demonstrate the energy saving efficiency of the proposed method.
{"title":"Optimal motion planning for minimizing energy consumption of wheeled mobile robots","authors":"Roger Datouo, F. B. Motto, B. E. Zobo, A. Melingui, Ismail Bensekrane, R. Merzouki","doi":"10.1109/ROBIO.2017.8324742","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324742","url":null,"abstract":"This paper presents a novel approach of finding energy-efficient trajectories for mobile robots. The approach integrates new cost and heuristic functions into the conventional A∗ algorithm while considering ground conditions and obstacle positions. The resulting planner helps to manage obstacle avoidance and to choose intelligent displacements of the robot. A heuristic function with energy-related criterion is defined in order to generate energy-efficient paths. Splines continuity property is exploited to generate smoothed energy-paths. The optimal velocity profile for minimum travel time is found by solving Sequential Quadratic Problem. A series of simulations demonstrate the energy saving efficiency of the proposed method.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"404 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132476070","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324801
Zijian Dong, Delong Zhu, M. Meng
The ability to operate an elevator is significant for service robots to move freely inside a building and the elevator button recognition is placed as one of the most critical functions of this process. However, the variety of button styles, the different light conditions and the blurred images caused by the camera motion make this task difficult. To tackle this obstacle to achieve the robust real-time performance, a button recognition system is proposed based on the convolutional neural networks. In consideration of the diverse button shapes, a contour extraction algorithm and the noise filtering are specifically designed to avoid the exhaustive search and reduce the consumed time. Then the fine-tuned CNN model is trained on our established elevator button dataset to achieve a more reliable recognition performance comparing to the template matching methods. Besides, the arrangement pattern of buttons is utilized to deduce the missing buttons and correct mistakes. To verify our algorithm, we run our algorithm on a dataset of 5 distinct elevators. Our algorithm succeeds in localizing and recognizing 98% of the buttons in known elevators and 87.6% in unknown elevators and has an average speed of 3 frames per second.
{"title":"An autonomous elevator button recognition system based on convolutional neural networks","authors":"Zijian Dong, Delong Zhu, M. Meng","doi":"10.1109/ROBIO.2017.8324801","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324801","url":null,"abstract":"The ability to operate an elevator is significant for service robots to move freely inside a building and the elevator button recognition is placed as one of the most critical functions of this process. However, the variety of button styles, the different light conditions and the blurred images caused by the camera motion make this task difficult. To tackle this obstacle to achieve the robust real-time performance, a button recognition system is proposed based on the convolutional neural networks. In consideration of the diverse button shapes, a contour extraction algorithm and the noise filtering are specifically designed to avoid the exhaustive search and reduce the consumed time. Then the fine-tuned CNN model is trained on our established elevator button dataset to achieve a more reliable recognition performance comparing to the template matching methods. Besides, the arrangement pattern of buttons is utilized to deduce the missing buttons and correct mistakes. To verify our algorithm, we run our algorithm on a dataset of 5 distinct elevators. Our algorithm succeeds in localizing and recognizing 98% of the buttons in known elevators and 87.6% in unknown elevators and has an average speed of 3 frames per second.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132894984","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324563
Minjing Yu, Yong-Jin Liu, Charlie C. L. Wang
Self-reconfigurable modular robots (SRRobot) that can change their shape and function in different environments according to different tasks have caught a lot of attention recently. Most existing prototypes use professional electronic components with relatively expensive cost and high barrier of fabrication. In this paper, we present a low-cost SRRobot with double-cube modules. Our system is easy-to-build even for novices as all electric components are off-the-shelf and the structural components in plastics are made by 3D printing. To have a better design of interior structures, we first construct a design space for all feasible solutions that satisfy the constraints of fabrication. Then, an optimized solution is found by an objective function incorporating the factors of space utilization, structural sound-ness and assembly complexity. Thirty EasySRRobot modules are manufactured and assembled. The functionality of our algorithm is demonstrated by comparing an optimized interior design with other two feasible designs and realizing different motions on an EasySRRobot with four modules.
{"title":"EasySRRobot: An easy-to-build self-reconfigurable robot with optimized design","authors":"Minjing Yu, Yong-Jin Liu, Charlie C. L. Wang","doi":"10.1109/ROBIO.2017.8324563","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324563","url":null,"abstract":"Self-reconfigurable modular robots (SRRobot) that can change their shape and function in different environments according to different tasks have caught a lot of attention recently. Most existing prototypes use professional electronic components with relatively expensive cost and high barrier of fabrication. In this paper, we present a low-cost SRRobot with double-cube modules. Our system is easy-to-build even for novices as all electric components are off-the-shelf and the structural components in plastics are made by 3D printing. To have a better design of interior structures, we first construct a design space for all feasible solutions that satisfy the constraints of fabrication. Then, an optimized solution is found by an objective function incorporating the factors of space utilization, structural sound-ness and assembly complexity. Thirty EasySRRobot modules are manufactured and assembled. The functionality of our algorithm is demonstrated by comparing an optimized interior design with other two feasible designs and realizing different motions on an EasySRRobot with four modules.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127993557","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324495
M. Souissi, Walid Amokrane, G. Poisson
This paper deals with 2D, and 3D simulations of a human equipped with back bone pitch and roll joints to study the advantages of having such a mechanism for daily human-like movements. A comparison between a normal spine and deformed spine due to scoliosis is made. The contribution of this paper consists of designing the mechanism for correcting abnormal postures of the human spine, taking into account the specifications of forward, backward and left/right sideways bending amplitudes. The mechanism is 2 legs mechanism composed of a bottom platform and a top platform connected by two articulated arms and a vertical central rod.
{"title":"Design and simulation of spine affected by scoliosis and proposition of dynamic brace","authors":"M. Souissi, Walid Amokrane, G. Poisson","doi":"10.1109/ROBIO.2017.8324495","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324495","url":null,"abstract":"This paper deals with 2D, and 3D simulations of a human equipped with back bone pitch and roll joints to study the advantages of having such a mechanism for daily human-like movements. A comparison between a normal spine and deformed spine due to scoliosis is made. The contribution of this paper consists of designing the mechanism for correcting abnormal postures of the human spine, taking into account the specifications of forward, backward and left/right sideways bending amplitudes. The mechanism is 2 legs mechanism composed of a bottom platform and a top platform connected by two articulated arms and a vertical central rod.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129259118","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324411
Chule Yang, Yijie Zeng, Yufeng Yue, Prarinya Siritanawan, Jun Zhang, Danwei W. Wang
Role recognition is a key problem when dealing with the unspecified human target whose description is limited, or appearance is ambiguous. Moreover, the ability to recognize the role of human can help to spot out the exceptional person in the scene. In this paper, a knowledge-based inference approach is proposed to categorize human roles as a binary representation of the targeted person and others by using the object-interaction feature and spatio-temporal feature. The method can associate spatial observations with prior knowledge and efficiently infer the role. An intelligent system equipped with an RGB-D sensor is employed to detect the individual and designated objects. Then, a probabilistic model of the existence of objects and human action is built based on prior knowledge. Finally, the system can determine the role through a Bayesian inference network. Experiments are conducted in multiple environments concerning different setups and degrees of clutter. The results show that the proposed method outperforms other methods regarding accuracy and robustness, moreover, exhibits a stable performance even in complex scenes.
{"title":"Knowledge-based role recognition by using human-object interaction and spatio-temporal analysis","authors":"Chule Yang, Yijie Zeng, Yufeng Yue, Prarinya Siritanawan, Jun Zhang, Danwei W. Wang","doi":"10.1109/ROBIO.2017.8324411","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324411","url":null,"abstract":"Role recognition is a key problem when dealing with the unspecified human target whose description is limited, or appearance is ambiguous. Moreover, the ability to recognize the role of human can help to spot out the exceptional person in the scene. In this paper, a knowledge-based inference approach is proposed to categorize human roles as a binary representation of the targeted person and others by using the object-interaction feature and spatio-temporal feature. The method can associate spatial observations with prior knowledge and efficiently infer the role. An intelligent system equipped with an RGB-D sensor is employed to detect the individual and designated objects. Then, a probabilistic model of the existence of objects and human action is built based on prior knowledge. Finally, the system can determine the role through a Bayesian inference network. Experiments are conducted in multiple environments concerning different setups and degrees of clutter. The results show that the proposed method outperforms other methods regarding accuracy and robustness, moreover, exhibits a stable performance even in complex scenes.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125568477","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324760
Guofei Zheng, Huaqing Min, Sheng Bi, Min Dong, Kaihong Yang
This paper designe a speech classifier based on compressive sensing (CS) measurement sequence which mainly solves the problem controlling robot and other intelligent equipments in the environment where we only need to use simple voice commands. In this paper, we obtain speech signal measurement sequence by using the row ladder matrix, then extract Mel Frequency Cepstral Coefficient (MFCC) matrix and reshape it into one-dimensional features. Moreover, we respectively obtain the classification model by using Supported Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithm. Experiments show that the highest accuracy rate of classifier up to 95% by using the KNN with Cosine distance model after that we tested for different distance models, and the accuracy rate is 91.95% by using the C-Support Vector Classification (C-SVC) of SVM classifier.
{"title":"Speech classification based on compressive sensing measurement sequence","authors":"Guofei Zheng, Huaqing Min, Sheng Bi, Min Dong, Kaihong Yang","doi":"10.1109/ROBIO.2017.8324760","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324760","url":null,"abstract":"This paper designe a speech classifier based on compressive sensing (CS) measurement sequence which mainly solves the problem controlling robot and other intelligent equipments in the environment where we only need to use simple voice commands. In this paper, we obtain speech signal measurement sequence by using the row ladder matrix, then extract Mel Frequency Cepstral Coefficient (MFCC) matrix and reshape it into one-dimensional features. Moreover, we respectively obtain the classification model by using Supported Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithm. Experiments show that the highest accuracy rate of classifier up to 95% by using the KNN with Cosine distance model after that we tested for different distance models, and the accuracy rate is 91.95% by using the C-Support Vector Classification (C-SVC) of SVM classifier.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126708177","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324541
Ning Li, A. Yazdanpanah, G. Mancini, Jindong Tan
This paper introduces a most frontier solution for minimally invasive laparoscopic vision, an untethered insertable robotic surgical camera (sCAM) system. Several key technologies toward this fully insertable laparoscopic robotic camera characterized by no tethering wires or mechanical actuation linkages have been addressed. Non-contact transabdominal camera actuation is designed and operated in a stator-rotor manner borrowing the principle of spherical motors. Wireless video transmission and control communication running on onboard power have helped eliminate cumbersome tethering wires pertaining to most state-of-the-art designs and thus facilitated flexible camera in vivo mobility. Moreover, a proprietary Bluetooth low energy (BLE) application profile has been developed specifically for this camera, providing functional services in an energy-efficient reliable manner for wireless camera control. Finally, experimental results have verified basic functions of this untethered robotic laparoscopic camera and justified feasibility of the design.
{"title":"Initial design and results of an untethered insertable laparoscopic robotic surgical camera system","authors":"Ning Li, A. Yazdanpanah, G. Mancini, Jindong Tan","doi":"10.1109/ROBIO.2017.8324541","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324541","url":null,"abstract":"This paper introduces a most frontier solution for minimally invasive laparoscopic vision, an untethered insertable robotic surgical camera (sCAM) system. Several key technologies toward this fully insertable laparoscopic robotic camera characterized by no tethering wires or mechanical actuation linkages have been addressed. Non-contact transabdominal camera actuation is designed and operated in a stator-rotor manner borrowing the principle of spherical motors. Wireless video transmission and control communication running on onboard power have helped eliminate cumbersome tethering wires pertaining to most state-of-the-art designs and thus facilitated flexible camera in vivo mobility. Moreover, a proprietary Bluetooth low energy (BLE) application profile has been developed specifically for this camera, providing functional services in an energy-efficient reliable manner for wireless camera control. Finally, experimental results have verified basic functions of this untethered robotic laparoscopic camera and justified feasibility of the design.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123293221","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 : 2017-12-01DOI: 10.1109/ROBIO.2017.8324413
Yalcin Akin, Shouhei Shirafuji, J. Ota
This paper presents a novel method for estimating lumbar spinal motion using practical and simple measurements. Previous studies have investigated the measurement methods for the lumbar spine; however, none of the studies that use wearable measurement systems have calculated the exact velocity of each vertebra using a non-invasive method for measuring vertebral motion including translation. The purpose of this study is to establish and implement a method to estimate accurate vertebral motion using a non-invasive technique. In the proposed method, we estimate the motion of the vertebra by using a rigid body model of the spine. We observe the changes at the contact points between the two belts and the wearer's back. In this study, we show how to estimate the lumbar motion at each vertebra by using sensors to measure the shifting, bending, and contacting regions of the flat belt attached to the wearer's back. We also validate the estimation of the angular velocity of the vertebra by measuring the shift in the belt by using wires and potentiometers. This is an important part of estimating the accurate motion of the vertebra.
{"title":"Non-invasive estimation method for lumbar spinal motion using flat belts and wires","authors":"Yalcin Akin, Shouhei Shirafuji, J. Ota","doi":"10.1109/ROBIO.2017.8324413","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324413","url":null,"abstract":"This paper presents a novel method for estimating lumbar spinal motion using practical and simple measurements. Previous studies have investigated the measurement methods for the lumbar spine; however, none of the studies that use wearable measurement systems have calculated the exact velocity of each vertebra using a non-invasive method for measuring vertebral motion including translation. The purpose of this study is to establish and implement a method to estimate accurate vertebral motion using a non-invasive technique. In the proposed method, we estimate the motion of the vertebra by using a rigid body model of the spine. We observe the changes at the contact points between the two belts and the wearer's back. In this study, we show how to estimate the lumbar motion at each vertebra by using sensors to measure the shifting, bending, and contacting regions of the flat belt attached to the wearer's back. We also validate the estimation of the angular velocity of the vertebra by measuring the shift in the belt by using wires and potentiometers. This is an important part of estimating the accurate motion of the vertebra.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121550646","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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