Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536064
Jiakang Zhou, Bin Gao, Boyang Xue, Qinghua Huang
Ultrasound is widely employed in disease screening and diagnosis. However, ultrasound scanning requires experienced sonographers manually operating probes to search the lesions inside patients, which is unavailable in rural or remote areas. Recently, teleoperated ultrasound scanning systems are proposed to enable sonographers to conduct scanning and diagnosis remotely. Nevertheless, these systems cannot offer a good sense of operation. This paper proposed a teleoperated ultrasonic scanning allowing sonographers to control the remote scanning probe with a glove in real-time. It can significantly increase the sense of operation. Experiments show its feasibility and a good sense of operation. It is noteworthy that the system is potential and easy to upgrade.
{"title":"Real-time Interaction of a 7-DOF Robot for Teleoperated Ultrasonic Scanning","authors":"Jiakang Zhou, Bin Gao, Boyang Xue, Qinghua Huang","doi":"10.1109/ICARM52023.2021.9536064","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536064","url":null,"abstract":"Ultrasound is widely employed in disease screening and diagnosis. However, ultrasound scanning requires experienced sonographers manually operating probes to search the lesions inside patients, which is unavailable in rural or remote areas. Recently, teleoperated ultrasound scanning systems are proposed to enable sonographers to conduct scanning and diagnosis remotely. Nevertheless, these systems cannot offer a good sense of operation. This paper proposed a teleoperated ultrasonic scanning allowing sonographers to control the remote scanning probe with a glove in real-time. It can significantly increase the sense of operation. Experiments show its feasibility and a good sense of operation. It is noteworthy that the system is potential and easy to upgrade.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115512990","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536127
Yu Chen, Xinde Li, S. Ge
Target positioning of a large inclination angle in aerial images is challenging for camera distortion, which makes it difficult to obtain a positioning model. Oblique images produce a larger positioning error if a traditional positioning algorithm is directly used to locate the target. To address this problem, this study uses a BP neural network to automatically calculate the high-accuracy positioning of the target. The location algorithm not only does not require camera calibration in advance but also eliminates the impact of camera distortion on target positioning. Through positioning experiments on the collected aerial dataset, the results demonstrate that the average positioning error of the target is about 1m, which has a high-precision positioning result and algorithm robustness.
{"title":"Research on the Algorithm of Target Location in Aerial Images under a Large Inclination Angle","authors":"Yu Chen, Xinde Li, S. Ge","doi":"10.1109/ICARM52023.2021.9536127","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536127","url":null,"abstract":"Target positioning of a large inclination angle in aerial images is challenging for camera distortion, which makes it difficult to obtain a positioning model. Oblique images produce a larger positioning error if a traditional positioning algorithm is directly used to locate the target. To address this problem, this study uses a BP neural network to automatically calculate the high-accuracy positioning of the target. The location algorithm not only does not require camera calibration in advance but also eliminates the impact of camera distortion on target positioning. Through positioning experiments on the collected aerial dataset, the results demonstrate that the average positioning error of the target is about 1m, which has a high-precision positioning result and algorithm robustness.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125989407","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}
Deep Reinforcement Learning (DRL) has made a great progress in recent years with the development of many relative researching areas, such as Deep Learning. Researchers have trained agents to achieve human-level and even beyond human-level scores in video games by using DRL. In the field of robotics, DRL can also achieve satisfactory performance for the navigation task when the environment is relatively simple. However, when environments become complex, e.g., the detour ones, the DRL system often fails to attain good results. To tackle this problem, we propose an internal reward obtaining method called New-Field-Explore (NFE) mechanism which can navigate a robot from initial position to target position without collision in detour environments. We also present a benchmark suite based on the AI2-Thor environment for robot navigation in complex detour environments. The proposed method is evaluated in these environments by comparing the performance of state-of-the-art algorithms with or without the NFE mechanism1. Experimental results show the above reward is effective for mobile robot navigation tasks in detour indoor environments.
{"title":"Deep Reinforcement Learning with New-Field Exploration for Navigation in Detour Environment","authors":"Jian Jiang, Junzhe Xu, Jianhua Zhang, Shengyong Chen","doi":"10.1109/ICARM52023.2021.9536098","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536098","url":null,"abstract":"Deep Reinforcement Learning (DRL) has made a great progress in recent years with the development of many relative researching areas, such as Deep Learning. Researchers have trained agents to achieve human-level and even beyond human-level scores in video games by using DRL. In the field of robotics, DRL can also achieve satisfactory performance for the navigation task when the environment is relatively simple. However, when environments become complex, e.g., the detour ones, the DRL system often fails to attain good results. To tackle this problem, we propose an internal reward obtaining method called New-Field-Explore (NFE) mechanism which can navigate a robot from initial position to target position without collision in detour environments. We also present a benchmark suite based on the AI2-Thor environment for robot navigation in complex detour environments. The proposed method is evaluated in these environments by comparing the performance of state-of-the-art algorithms with or without the NFE mechanism1. Experimental results show the above reward is effective for mobile robot navigation tasks in detour indoor environments.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194327","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536143
Xiangyang Zhou, Xinping Dai, Yating Li
The three-axis inertially stabilized platform (ISP) can effectively isolation disturbance inside and outside the aircraft, and create a stable working environment for the aerial remote sensing system. ISP usually uses three-axis frame structure to isolate the aircraft attitude angle motion, but the frame coupling effect has an important effect on the high-accuracy control of the ISP. In this essay, method of adaptive composite decoupling controller on the basis of inverse system model reference is came forward to realize the high-accuracy decoupling control of the three-axis ISP.
{"title":"Nonlinear Dynamics Decoupling Control for a Light and Small Inertially Stabilized Platform*","authors":"Xiangyang Zhou, Xinping Dai, Yating Li","doi":"10.1109/ICARM52023.2021.9536143","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536143","url":null,"abstract":"The three-axis inertially stabilized platform (ISP) can effectively isolation disturbance inside and outside the aircraft, and create a stable working environment for the aerial remote sensing system. ISP usually uses three-axis frame structure to isolate the aircraft attitude angle motion, but the frame coupling effect has an important effect on the high-accuracy control of the ISP. In this essay, method of adaptive composite decoupling controller on the basis of inverse system model reference is came forward to realize the high-accuracy decoupling control of the three-axis ISP.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126588307","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536183
Jin Huang, Guoxin Li, Qingsheng Meng, H. Xia, Yueyue Liu, Zhijun Li
Replacing the human upper limb with artificial devices of equal capability and effectiveness is a long-standing challenge. In this paper, a hybrid reach-to-grasp task planning scheme is proposed for transhumeral amputees exploiting both electromyography (EMG) and visual signals to control the upper limb prosthesis. EMG signals extracted from the subject are fed into the long short-term memery neural network to control the motion of the prosthesis after training and classification. The visual servoing module intends to detect and locate the object thus estimate grasping pattern in real time. In our control strategy, amputees are able to use the EMG signals to operate the prosthesis, and they can also activate the visual module at any moment, which recognizes and locates the object to be grabbed, and then moves the prosthesis close to the object and imposes grasping according the preset inference library, which reduces the cognitive and operational burden of amputees greatly. Finally, experiments are conducted on a patient with transhumeral left arm amputation to verify the effectiveness of the proposed control strategy using a upper limb prosthesis. The results showed that the hybrid control scheme brings more choices to control the prosthesis freely and flexibly.
{"title":"Development and Hybrid Control of an Upper Limb Prosthesis for Reach and Grasp Motions","authors":"Jin Huang, Guoxin Li, Qingsheng Meng, H. Xia, Yueyue Liu, Zhijun Li","doi":"10.1109/ICARM52023.2021.9536183","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536183","url":null,"abstract":"Replacing the human upper limb with artificial devices of equal capability and effectiveness is a long-standing challenge. In this paper, a hybrid reach-to-grasp task planning scheme is proposed for transhumeral amputees exploiting both electromyography (EMG) and visual signals to control the upper limb prosthesis. EMG signals extracted from the subject are fed into the long short-term memery neural network to control the motion of the prosthesis after training and classification. The visual servoing module intends to detect and locate the object thus estimate grasping pattern in real time. In our control strategy, amputees are able to use the EMG signals to operate the prosthesis, and they can also activate the visual module at any moment, which recognizes and locates the object to be grabbed, and then moves the prosthesis close to the object and imposes grasping according the preset inference library, which reduces the cognitive and operational burden of amputees greatly. Finally, experiments are conducted on a patient with transhumeral left arm amputation to verify the effectiveness of the proposed control strategy using a upper limb prosthesis. The results showed that the hybrid control scheme brings more choices to control the prosthesis freely and flexibly.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126501994","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536052
H. Cheng, Siyuan Liu, De-yuan Meng
Robots are widely used in the field of medical rehabilitation to assist patients to conduct rehabilitation training. Due to the repetition nature of the rehabilitation training, this paper proposes an iterative learning controller equipped with feedback mechanism for the passive hand rehabilitation training, which is based on a cable-driven hand exoskeleton robot. Thanks to the use of the information from previous iterations, the desired trajectory can be perfectly tracked over a finite duration. Moreover, the monotonic convergence of the proposed iterative learning controller can be achieved under a sufficient condition. In addition, our iterative learning controller is applied to the hand exoskeleton robot in both the simulation tests and the physical trajectory tracking experiments, which demonstrates its effectiveness and desired control performance.
{"title":"Passive Hand Rehabilitation Training Through Robots: an Iterative Learning Control Approach","authors":"H. Cheng, Siyuan Liu, De-yuan Meng","doi":"10.1109/ICARM52023.2021.9536052","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536052","url":null,"abstract":"Robots are widely used in the field of medical rehabilitation to assist patients to conduct rehabilitation training. Due to the repetition nature of the rehabilitation training, this paper proposes an iterative learning controller equipped with feedback mechanism for the passive hand rehabilitation training, which is based on a cable-driven hand exoskeleton robot. Thanks to the use of the information from previous iterations, the desired trajectory can be perfectly tracked over a finite duration. Moreover, the monotonic convergence of the proposed iterative learning controller can be achieved under a sufficient condition. In addition, our iterative learning controller is applied to the hand exoskeleton robot in both the simulation tests and the physical trajectory tracking experiments, which demonstrates its effectiveness and desired control performance.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"85 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131779440","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536122
Xiaozhi Zhang, Zhongtao Fu, Guangwei Wang
This paper presents the design and analysis of a novel polishing robotic end-effector with 3-degree-of-freedom(3DOF) based on parallel decoupling flexure mechanism(PDFM). The PDFM provides a complaint contact environment between the polishing tool head and workpiece surface to cut down the impact and backlash. Besides, the deformation of the flexure hinges in PDFM is used to measure the contact force with the strain gauge. Based on the force feedback control, the polishing robot with the end-effector can obtain minimum surface roughness and better surface morphology. To describe the relationship between the contact force and deformation of the flexure hinges in PDFM, the pseudo rigid body model is employed. To evaluate the accuracy of the modeling result, the FEA simulation is carried out. The load capacity testing and modal simulation study are conducted to test the performance of end-effector.Note to Practitioners—The motivation of this work is to develop a 3-DOF strictly parallel polishing robot end-effector. A novel parallel-kinematic PDFM with strain gauge are developed. The end-effector owns the independent movement along three axes and large bear capacity. Analytical modeling and simulation study are carried out to validate the performance of the proposed design. Results demonstrate the fine decoupling property of the designed end-effector.
{"title":"Design and Development of a Novel 3-DOF Parallel Robotic Polishing End-effector","authors":"Xiaozhi Zhang, Zhongtao Fu, Guangwei Wang","doi":"10.1109/ICARM52023.2021.9536122","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536122","url":null,"abstract":"This paper presents the design and analysis of a novel polishing robotic end-effector with 3-degree-of-freedom(3DOF) based on parallel decoupling flexure mechanism(PDFM). The PDFM provides a complaint contact environment between the polishing tool head and workpiece surface to cut down the impact and backlash. Besides, the deformation of the flexure hinges in PDFM is used to measure the contact force with the strain gauge. Based on the force feedback control, the polishing robot with the end-effector can obtain minimum surface roughness and better surface morphology. To describe the relationship between the contact force and deformation of the flexure hinges in PDFM, the pseudo rigid body model is employed. To evaluate the accuracy of the modeling result, the FEA simulation is carried out. The load capacity testing and modal simulation study are conducted to test the performance of end-effector.Note to Practitioners—The motivation of this work is to develop a 3-DOF strictly parallel polishing robot end-effector. A novel parallel-kinematic PDFM with strain gauge are developed. The end-effector owns the independent movement along three axes and large bear capacity. Analytical modeling and simulation study are carried out to validate the performance of the proposed design. Results demonstrate the fine decoupling property of the designed end-effector.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128260316","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536178
Jin Zhang, Honglei An, Yongshan Huang, Qing Wei, Hongxu Ma
The gait switching ability is one of the important indicators for the practical application of prosthetic limbs, but there is little research on it. This paper proposes a prosthetic gait switching strategy based on phase estimation for smooth gait transition from flat to upstairs. Firstly, the current gait category was identified by the hip Angle features (median and amplitude), and the gait transition from plane to upstairs was carried out based on the smooth change of gait. Later, with the Improved Kalman filter (IKF) to estimate gait phase, the current state’s position in the whole gait can be obtained. Then input phase into gaussian process (GP) under different gait function prediction of knee joint angle, and combined with the gait feature to get the current need of knee joint angle, so the prosthesis can be controlled. This paper compared the predicted trajectory with the collected data and found that this method could predict the knee joint angle good in the process of gait change. Finally, by comparing the phase prediction trajectory before and after filtering, this paper finds that the phase prediction trajectory after filtering has better effect and smaller error.
{"title":"Flat-Upstairs Gait Switching of Lower Limb Prosthesis via Gaussian Process and Improved Kalman Filter","authors":"Jin Zhang, Honglei An, Yongshan Huang, Qing Wei, Hongxu Ma","doi":"10.1109/ICARM52023.2021.9536178","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536178","url":null,"abstract":"The gait switching ability is one of the important indicators for the practical application of prosthetic limbs, but there is little research on it. This paper proposes a prosthetic gait switching strategy based on phase estimation for smooth gait transition from flat to upstairs. Firstly, the current gait category was identified by the hip Angle features (median and amplitude), and the gait transition from plane to upstairs was carried out based on the smooth change of gait. Later, with the Improved Kalman filter (IKF) to estimate gait phase, the current state’s position in the whole gait can be obtained. Then input phase into gaussian process (GP) under different gait function prediction of knee joint angle, and combined with the gait feature to get the current need of knee joint angle, so the prosthesis can be controlled. This paper compared the predicted trajectory with the collected data and found that this method could predict the knee joint angle good in the process of gait change. Finally, by comparing the phase prediction trajectory before and after filtering, this paper finds that the phase prediction trajectory after filtering has better effect and smaller error.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128393958","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536058
Renyu Yang, Jie Zhou, R. Song
Compliant, natural and safe physical human-robot interaction is of practical significance for rehabilitation robots. In our recently developed lower limb rehabilitation robot (LLRR), an adaptive admittance control based on linear quadratic regulation (LQR) optimization technique was designed to regulate parameters synchronously with the variable impedance property of human-robot interactive system. Firstly, a computed torque PD control was designed to guarantee the accuracy and stability of trajectory tracking. Secondly, an observer was designed to estimate human-robot interaction torque (HRIT) during cooperative task. Finally, a LQR optimization technique was employed to optimize admittance model parameters and minimize tracking errors and human efforts. Simulation studies were conducted on the LLRR and the results show that the HRIT can be estimated by the observer correctly and the desired trajectory was deformed smoothly and rightly with the interaction torque.
{"title":"Adaptive Admittance Control Based on Linear Quadratic Regulation Optimization Technique for a Lower Limb Rehabilitation Robot*","authors":"Renyu Yang, Jie Zhou, R. Song","doi":"10.1109/ICARM52023.2021.9536058","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536058","url":null,"abstract":"Compliant, natural and safe physical human-robot interaction is of practical significance for rehabilitation robots. In our recently developed lower limb rehabilitation robot (LLRR), an adaptive admittance control based on linear quadratic regulation (LQR) optimization technique was designed to regulate parameters synchronously with the variable impedance property of human-robot interactive system. Firstly, a computed torque PD control was designed to guarantee the accuracy and stability of trajectory tracking. Secondly, an observer was designed to estimate human-robot interaction torque (HRIT) during cooperative task. Finally, a LQR optimization technique was employed to optimize admittance model parameters and minimize tracking errors and human efforts. Simulation studies were conducted on the LLRR and the results show that the HRIT can be estimated by the observer correctly and the desired trajectory was deformed smoothly and rightly with the interaction torque.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131177564","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 : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536209
Yongshan Huang, Hongxu Ma, Jin Zhang, Honglei An
A ground reaction forces (GRFs) estimation method based on super-twisting extended state observer (STESO) for robotic prosthesis is proposed. The load cells and pressure sensors are not needed for the proposed method, and also the model of GRFs, hence it could adapt to different terrain environments. The GRFs estimate method uses a globally integral and super-twisting sliding model, which enables the observation error to converge to zero in finite time, and the GRFs estimator would not crash even if the initial estimation error is large. The stability and finite time convergence of the observer is rigorously proved and analyzed mathematically. The simulation results prove the feasibility and effectiveness of the proposed GRFs estimates method.
{"title":"Ground Reaction Force Estimation in Robotic Prosthesis using Super-twisting Extended State Observer","authors":"Yongshan Huang, Hongxu Ma, Jin Zhang, Honglei An","doi":"10.1109/ICARM52023.2021.9536209","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536209","url":null,"abstract":"A ground reaction forces (GRFs) estimation method based on super-twisting extended state observer (STESO) for robotic prosthesis is proposed. The load cells and pressure sensors are not needed for the proposed method, and also the model of GRFs, hence it could adapt to different terrain environments. The GRFs estimate method uses a globally integral and super-twisting sliding model, which enables the observation error to converge to zero in finite time, and the GRFs estimator would not crash even if the initial estimation error is large. The stability and finite time convergence of the observer is rigorously proved and analyzed mathematically. The simulation results prove the feasibility and effectiveness of the proposed GRFs estimates method.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133872570","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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