Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354835
Yuhui Cen, Jingjing Luo, Hongbo Wang, Li Chen, Xing Zhu, Jingchun Luo
Blood pressure (BP) estimation through cuffless approaches is gaining prominence in precision healthcare, and the emergence of robotic medical services adds impetus to this trend with enhanced diagnostic capabilities. In our endeavor to enable medical service robots for cuffless BP self-estimation, we propose OCViTnet, a deep-learning network model grounded in pulse wave analysis (PWA). The model introduces a novel waveform processing architecture: an omni-scale convolution subnet captures single-period waveform characteristics, the Vision Transformer subnet extracts multi-period waveform features, and a regressor fuses phenotypic information with pulse wave features and performs BP regression. Experimental results perform exceptionally well in non-contact BP estimation from forehead imaging photoplethysmography. Additionally, this paper pioneers the utilization of the radial artery pulse wave for BP estimation. Leveraging the British Hypertension Society standard, our approach yields notable results, assessing the pulse diagnosis robot’s BP estimation performance at grade C/B (systolic/diastolic BP). This effort advances the potential of cuffless BP estimation in pulse diagnosis robotics and underscores the practical viability of our proposed intelligent methodology based on PWA.
{"title":"OCViTnet: Pulse Wave Learning for Cuffless Blood Pressure Estimation of Medical Service Robots","authors":"Yuhui Cen, Jingjing Luo, Hongbo Wang, Li Chen, Xing Zhu, Jingchun Luo","doi":"10.1109/ROBIO58561.2023.10354835","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354835","url":null,"abstract":"Blood pressure (BP) estimation through cuffless approaches is gaining prominence in precision healthcare, and the emergence of robotic medical services adds impetus to this trend with enhanced diagnostic capabilities. In our endeavor to enable medical service robots for cuffless BP self-estimation, we propose OCViTnet, a deep-learning network model grounded in pulse wave analysis (PWA). The model introduces a novel waveform processing architecture: an omni-scale convolution subnet captures single-period waveform characteristics, the Vision Transformer subnet extracts multi-period waveform features, and a regressor fuses phenotypic information with pulse wave features and performs BP regression. Experimental results perform exceptionally well in non-contact BP estimation from forehead imaging photoplethysmography. Additionally, this paper pioneers the utilization of the radial artery pulse wave for BP estimation. Leveraging the British Hypertension Society standard, our approach yields notable results, assessing the pulse diagnosis robot’s BP estimation performance at grade C/B (systolic/diastolic BP). This effort advances the potential of cuffless BP estimation in pulse diagnosis robotics and underscores the practical viability of our proposed intelligent methodology based on PWA.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"83 3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187069","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354632
Lei Yao, Bing Chen, Moyun Liu, Jingming Xie, Youping Chen, Lei He
Kinesthetic demonstration requires accurate force/torque measurements from sensors. However, even in static conditions, the sensor readings exhibit non-zero fluctuations, which can lead to unstable force control and impair the quality of kinesthetic demonstration. In this paper, we refer to the above problem as phantom zeros and systematically analyze factors contributing to their variability of a traction force sensor. Neural networks (NN) are first introduced to model the complex nonlinear mapping between sensor orientations and phantom zeros. The initial parameters of the NN are then optimized using a genetic algorithm (GA) to prevent convergence to local optima and improve modeling accuracy. In addition, we develop an experimental platform with a physical UR10 robot and a custom traction sensor to comprehensively evaluate the proposed approach. Results demonstrate that the GA-optimized NN achieves higher precision and robustness in predicting phantom zeros under different orientations compared to least squares and vanilla NN baselines. By modeling and predicting phantom zeros, the proposed method can filter out phantom force fluctuations during kinesthetic demonstration, while preserving critical motion information. This work provides insights into modeling and mitigating force/torque sensor uncertainties for enabling more precise robot control and interactive guidance.
体感演示需要传感器对力/力矩进行精确测量。然而，即使在静态条件下，传感器读数也会出现非零波动，这可能会导致力控制不稳定，影响动感演示的质量。在本文中，我们将上述问题称为幻影零点，并系统分析了导致牵引力传感器变化的因素。首先引入神经网络（NN）来模拟传感器方向和幽灵零点之间复杂的非线性映射。然后使用遗传算法（GA）优化神经网络的初始参数，以防止收敛到局部最优并提高建模精度。此外，我们还利用物理 UR10 机器人和定制牵引传感器开发了一个实验平台，以全面评估所提出的方法。结果表明，与最小二乘法和普通 NN 基线相比，经过 GA 优化的 NN 在预测不同方向的幻影零点时具有更高的精度和鲁棒性。通过对幻影零点进行建模和预测，所提出的方法可以在动觉演示过程中过滤掉幻影力波动，同时保留关键的运动信息。这项工作为力/力矩传感器不确定性的建模和缓解提供了见解，从而实现更精确的机器人控制和交互式引导。
{"title":"A Data-Driven Phantom Zeros Prediction Algorithm for Traction Force Sensor in Kinesthetic Demonstration","authors":"Lei Yao, Bing Chen, Moyun Liu, Jingming Xie, Youping Chen, Lei He","doi":"10.1109/ROBIO58561.2023.10354632","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354632","url":null,"abstract":"Kinesthetic demonstration requires accurate force/torque measurements from sensors. However, even in static conditions, the sensor readings exhibit non-zero fluctuations, which can lead to unstable force control and impair the quality of kinesthetic demonstration. In this paper, we refer to the above problem as phantom zeros and systematically analyze factors contributing to their variability of a traction force sensor. Neural networks (NN) are first introduced to model the complex nonlinear mapping between sensor orientations and phantom zeros. The initial parameters of the NN are then optimized using a genetic algorithm (GA) to prevent convergence to local optima and improve modeling accuracy. In addition, we develop an experimental platform with a physical UR10 robot and a custom traction sensor to comprehensively evaluate the proposed approach. Results demonstrate that the GA-optimized NN achieves higher precision and robustness in predicting phantom zeros under different orientations compared to least squares and vanilla NN baselines. By modeling and predicting phantom zeros, the proposed method can filter out phantom force fluctuations during kinesthetic demonstration, while preserving critical motion information. This work provides insights into modeling and mitigating force/torque sensor uncertainties for enabling more precise robot control and interactive guidance.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"59 12","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187093","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354613
Haotian Li, Yuxiang Sun
Semantic scene understanding is a fundamental task for autonomous driving. It serves as a build block for many downstream tasks. Under challenging illumination conditions, thermal images can provide complementary information for RGB images. Many multi-modal fusion networks have been proposed using RGB-Thermal data for semantic scene understanding. However, current state-of-the-art methods simply use networks to fuse features on multi-modality inexplicably, rather than designing a fusion method based on the intrinsic characteristics of RGB images and thermal images. To address this issue, we propose IGFNet, an illumination-guided fusion network for RGB-Thermal semantic scene understanding, which utilizes a weight mask generated by the illumination estimation module to weight the RGB and thermal feature maps at different stages. Experimental results show that our network outperforms the state-of-the-art methods on the MFNet dataset. Our code is available at: https://github.com/lab-sun/IGFNet.
{"title":"IGFNet: Illumination-Guided Fusion Network for Semantic Scene Understanding using RGB-Thermal Images","authors":"Haotian Li, Yuxiang Sun","doi":"10.1109/ROBIO58561.2023.10354613","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354613","url":null,"abstract":"Semantic scene understanding is a fundamental task for autonomous driving. It serves as a build block for many downstream tasks. Under challenging illumination conditions, thermal images can provide complementary information for RGB images. Many multi-modal fusion networks have been proposed using RGB-Thermal data for semantic scene understanding. However, current state-of-the-art methods simply use networks to fuse features on multi-modality inexplicably, rather than designing a fusion method based on the intrinsic characteristics of RGB images and thermal images. To address this issue, we propose IGFNet, an illumination-guided fusion network for RGB-Thermal semantic scene understanding, which utilizes a weight mask generated by the illumination estimation module to weight the RGB and thermal feature maps at different stages. Experimental results show that our network outperforms the state-of-the-art methods on the MFNet dataset. Our code is available at: https://github.com/lab-sun/IGFNet.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"81 6","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187101","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}
Bronchoscopy is widely used as a minimally invasive diagnostic and therapeutic modality for early screening of bronchial diseases. To face the complicated airway structure and gradually decreasing bronchial diameter with increasing generation, the bronchoscope with enhanced steering capability is more competent. In this paper, a spring-based miniature extensible manipulator is proposed as the active bending segment for the bronchoscope based on the detailed problem statement about the steering ability. The manipulator, which takes advantage of the extension of the compression spring, features a simple structural design, offset neutral bending plane and extensibility. The associated kinematics based on the piecewise constant curvature model are presented in detail. To validate the concept, a manipulator prototype with an outer diameter of 4 mm and the custom actuation device with a constrained mechanism for the driven rod is fabricated. Several experiments including motion validation, kinematics validation, and steering capability validation are performed, and the results indicate that the proposed manipulator system is feasible and has the potential to improve bronchoscopic steering capability and to further improve diagnostic yield.
{"title":"Preliminary Study of a Spring-Based Miniature Extensible Manipulator for Bronchoscopic Steering","authors":"Jie Wang, Chengquan Hu, Yihua Sun, Longfei Ma, Guochen Ning, Hongen Liao","doi":"10.1109/ROBIO58561.2023.10354864","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354864","url":null,"abstract":"Bronchoscopy is widely used as a minimally invasive diagnostic and therapeutic modality for early screening of bronchial diseases. To face the complicated airway structure and gradually decreasing bronchial diameter with increasing generation, the bronchoscope with enhanced steering capability is more competent. In this paper, a spring-based miniature extensible manipulator is proposed as the active bending segment for the bronchoscope based on the detailed problem statement about the steering ability. The manipulator, which takes advantage of the extension of the compression spring, features a simple structural design, offset neutral bending plane and extensibility. The associated kinematics based on the piecewise constant curvature model are presented in detail. To validate the concept, a manipulator prototype with an outer diameter of 4 mm and the custom actuation device with a constrained mechanism for the driven rod is fabricated. Several experiments including motion validation, kinematics validation, and steering capability validation are performed, and the results indicate that the proposed manipulator system is feasible and has the potential to improve bronchoscopic steering capability and to further improve diagnostic yield.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"69 5","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187121","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354666
Xu Li, Yili Fu
This paper introduces the design and experimental evaluation of WLR-III, which stands for the third-generation hydraulic wheel-legged robot. WLR-III is expected to be applied to disaster scenarios where the mobility, adaptability and manipulation capability are required. Based on the development of the previous two generations of wheel-legged robots, this work continuously optimizes the design to achieve higher mobility and stronger adaptability by reducing weight & inertia. The hydraulic power transmission system adopts a hose-less design method to ensure the robustness of the system. What's more prominent is that the successful development of hydraulic power unit (HPU) enables WLR-III to realize hydraulic power autonomy. In addition, to accomplish all kinds of operational tasks in the rescue scene, the electro-hydraulic hybrid drives anthropomorphic arms with heavy load grippers were developed. Finally, the effectiveness and reliability of design optimization have been evaluated through a series of experiments, including grassland movement, load bearing, obstacle-stepping and tool-operating. To the authors' best knowledge, this is the first time that a hydraulic powered autonomous wheel-legged humanoid robot with the ability to operate simple tools has been developed.
{"title":"Design and Experimental Evaluation of WLR-III","authors":"Xu Li, Yili Fu","doi":"10.1109/ROBIO58561.2023.10354666","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354666","url":null,"abstract":"This paper introduces the design and experimental evaluation of WLR-III, which stands for the third-generation hydraulic wheel-legged robot. WLR-III is expected to be applied to disaster scenarios where the mobility, adaptability and manipulation capability are required. Based on the development of the previous two generations of wheel-legged robots, this work continuously optimizes the design to achieve higher mobility and stronger adaptability by reducing weight & inertia. The hydraulic power transmission system adopts a hose-less design method to ensure the robustness of the system. What's more prominent is that the successful development of hydraulic power unit (HPU) enables WLR-III to realize hydraulic power autonomy. In addition, to accomplish all kinds of operational tasks in the rescue scene, the electro-hydraulic hybrid drives anthropomorphic arms with heavy load grippers were developed. Finally, the effectiveness and reliability of design optimization have been evaluated through a series of experiments, including grassland movement, load bearing, obstacle-stepping and tool-operating. To the authors' best knowledge, this is the first time that a hydraulic powered autonomous wheel-legged humanoid robot with the ability to operate simple tools has been developed.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"69 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187122","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354695
Zhaoyu Zhang, Haibin Duan
This paper focuses on the autonomous navigation problem of the fixed-wing aerial robot, of which the inertial measurement unit (IMU) has time-varying error characteristic parameters. A robust variational Bayesian adaptive Kalman filter (RVBAKF) is proposed to tackle the noise outliers in integrated navigation brought by sensor uncertainties. The proposed method formulates the joint probability distribution of the system state vector and the measurement noise covariance matrix. A fading factor matrix with strong tracking quality is introduced to enhance the prediction on the prior distribution of the process noise covariance. Then a weighted sliding window mechanism has been constructed to obtain the posterior distribution of the measurement noise outliers. Therefore, the proposed approach is impressive in approximating both the process and measurement noise. The RVBAKF algorithm is implemented in an integrated navigation system which is composed of the strapdown inertial navigation system (SINS) and the global navigation satellite system (GNSS). The integration framework based on RVBAKF is conducted on two typical verification scenarios, which is proven to be exceptional in coping with the time-varying process and measurement noise by comparing the average root mean square error in misalignment angle, velocity and position with the strong tracking filter and the variational Bayesian filter.
{"title":"Robust Adaptive Filter for Time-Varying Parameters Estimation in Integrated Navigation of Fixed-Wing Aerial Robot*","authors":"Zhaoyu Zhang, Haibin Duan","doi":"10.1109/ROBIO58561.2023.10354695","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354695","url":null,"abstract":"This paper focuses on the autonomous navigation problem of the fixed-wing aerial robot, of which the inertial measurement unit (IMU) has time-varying error characteristic parameters. A robust variational Bayesian adaptive Kalman filter (RVBAKF) is proposed to tackle the noise outliers in integrated navigation brought by sensor uncertainties. The proposed method formulates the joint probability distribution of the system state vector and the measurement noise covariance matrix. A fading factor matrix with strong tracking quality is introduced to enhance the prediction on the prior distribution of the process noise covariance. Then a weighted sliding window mechanism has been constructed to obtain the posterior distribution of the measurement noise outliers. Therefore, the proposed approach is impressive in approximating both the process and measurement noise. The RVBAKF algorithm is implemented in an integrated navigation system which is composed of the strapdown inertial navigation system (SINS) and the global navigation satellite system (GNSS). The integration framework based on RVBAKF is conducted on two typical verification scenarios, which is proven to be exceptional in coping with the time-varying process and measurement noise by comparing the average root mean square error in misalignment angle, velocity and position with the strong tracking filter and the variational Bayesian filter.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"79 11","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187141","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354615
Xinyang Wang, Xuan Pei, Jiahao Wu, Xiangxing Wang, Taogang Hou
Water-jet propulsion helps flying squid shoot quickly from underwater into the air, overcoming the huge differences in density and viscosity between two fluids. To get faster underwater takeoff, water-jet propulsion can be great inspiration for the design of new propulsion system for aquatic unmanned aerial vehicle (AquaUAV). In this paper, an novel aerial-aquatic water-jet thruster is developed and fabricated, which uses butane and oxygen to realize explosive water-jet. An unit butane cell and oxygen cell can satisfy more than 50 explosions without replacement of components. We designed different fine-tuning strategies for the two gas supply, designed and completed experiments to obtain stable gas supply and controllable explosion. And the optimized supply systems were tested on the force measurement system. For the first time, our new thruster achieved underwater no-exchange-air explosion, which may help AquaUAV handle continuous underwater explosive propulsion and repeatable launches other than propellers.
{"title":"Design, fabrication and fine-tuning of an aerial-aquatic explosive water-jet thruster with repeatable propulsion capability","authors":"Xinyang Wang, Xuan Pei, Jiahao Wu, Xiangxing Wang, Taogang Hou","doi":"10.1109/ROBIO58561.2023.10354615","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354615","url":null,"abstract":"Water-jet propulsion helps flying squid shoot quickly from underwater into the air, overcoming the huge differences in density and viscosity between two fluids. To get faster underwater takeoff, water-jet propulsion can be great inspiration for the design of new propulsion system for aquatic unmanned aerial vehicle (AquaUAV). In this paper, an novel aerial-aquatic water-jet thruster is developed and fabricated, which uses butane and oxygen to realize explosive water-jet. An unit butane cell and oxygen cell can satisfy more than 50 explosions without replacement of components. We designed different fine-tuning strategies for the two gas supply, designed and completed experiments to obtain stable gas supply and controllable explosion. And the optimized supply systems were tested on the force measurement system. For the first time, our new thruster achieved underwater no-exchange-air explosion, which may help AquaUAV handle continuous underwater explosive propulsion and repeatable launches other than propellers.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"56 6","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187164","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}
Applying Wireless Sensor Networks(WSNs) to coal mine safety monitoring is an effective means to achieve continuous monitoring of underground environmental parameters, but how to deploy them is a prerequisite for application. Firstly, a three-dimensional deployment strategy based on Confident Information Coverage (CIC) model suitable for narrow and long underground spaces is proposed. Secondly, an autonomous deployment method for WSNs nodes in a multi robots system using robots as node carriers is proposed, which effectively improves the deployment efficiency of nodes. Finally, the deployment strategy and method proposed in this paper were validated through simulation experiments. The experimental results showed that the proposed strategy can reduce the number of nodes, and the deployment method is also superior to existing methods.
{"title":"Deployment Method of Wireless Sensor Networks for Coal Mine Safety Monitoring Based on Multi Robot Systems","authors":"Hongwei Tang, Gongbo Zhou, Deen Bai, Menggang Li, Xia Zhang, Chaoquan Tang","doi":"10.1109/ROBIO58561.2023.10354569","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354569","url":null,"abstract":"Applying Wireless Sensor Networks(WSNs) to coal mine safety monitoring is an effective means to achieve continuous monitoring of underground environmental parameters, but how to deploy them is a prerequisite for application. Firstly, a three-dimensional deployment strategy based on Confident Information Coverage (CIC) model suitable for narrow and long underground spaces is proposed. Secondly, an autonomous deployment method for WSNs nodes in a multi robots system using robots as node carriers is proposed, which effectively improves the deployment efficiency of nodes. Finally, the deployment strategy and method proposed in this paper were validated through simulation experiments. The experimental results showed that the proposed strategy can reduce the number of nodes, and the deployment method is also superior to existing methods.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"67 3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187184","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354606
Shipei Cao, Youliang Cheng, Bo Sheng, Jing Tao
In response to the deficiency of traditional rigid-driven exoskeletons, this paper presents the mechanical design and control strategy of a compact variable stiffness joint mechanism for modular lower limb assistive exoskeletons. The stiffness variation is achieved by modifying the lever arm principle, while allowing for adjustable configurations to cater to different stiffness requirements. The range of stiffness variation of the proposed joint is first mathematically modeled, and its stiffness characteristics, as well as the effects of different configurations, are then analyzed. In accordance to the mechanism design of the joint, a control strategy for a modular compliant lower limb assistive exoskeleton is proposed. The stiffness adjustment and output torque requirements are analyzed and modeled and a solution to control variables are derived for the 40% assistance case. The case study results indicate a relatively low coupling between the stiffness and torque of the mechanism.
{"title":"Design of a Compact Variable Stiffness Joint for Modular Lower Limb Assistive Exoskeleton","authors":"Shipei Cao, Youliang Cheng, Bo Sheng, Jing Tao","doi":"10.1109/ROBIO58561.2023.10354606","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354606","url":null,"abstract":"In response to the deficiency of traditional rigid-driven exoskeletons, this paper presents the mechanical design and control strategy of a compact variable stiffness joint mechanism for modular lower limb assistive exoskeletons. The stiffness variation is achieved by modifying the lever arm principle, while allowing for adjustable configurations to cater to different stiffness requirements. The range of stiffness variation of the proposed joint is first mathematically modeled, and its stiffness characteristics, as well as the effects of different configurations, are then analyzed. In accordance to the mechanism design of the joint, a control strategy for a modular compliant lower limb assistive exoskeleton is proposed. The stiffness adjustment and output torque requirements are analyzed and modeled and a solution to control variables are derived for the 40% assistance case. The case study results indicate a relatively low coupling between the stiffness and torque of the mechanism.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"66 6","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187187","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 : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354980
Qingsong Yu, Xiangrong Xu, Yinzhen Liu, Hui Zhang
Since the current grasping success rate of robots is low when performing grasping tasks in complex environments, in order to improve this problem, this paper proposes a robot grasping detection network SA-U2GNet combining U2-Net and Shuffle Attention networks. The network can not only achieve information communication between different sub-features through the attention mechanism, but also capture more contextual information from RGB-D images through the two-level nested U-shaped structure. Training and testing were performed on the Cornell and Jacquard grasp datasets, the accuracy rates reached 97.9% and 94.7% respectively, and the time required to process RGB-D images was 30ms. Compared with other methods, this method improves the accuracy and time efficiency, and the experiment verifies the feasibility and effectiveness of this method.
{"title":"Robot Plane Grasping Pose Detection Based on U2-Net","authors":"Qingsong Yu, Xiangrong Xu, Yinzhen Liu, Hui Zhang","doi":"10.1109/ROBIO58561.2023.10354980","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354980","url":null,"abstract":"Since the current grasping success rate of robots is low when performing grasping tasks in complex environments, in order to improve this problem, this paper proposes a robot grasping detection network SA-U2GNet combining U2-Net and Shuffle Attention networks. The network can not only achieve information communication between different sub-features through the attention mechanism, but also capture more contextual information from RGB-D images through the two-level nested U-shaped structure. Training and testing were performed on the Cornell and Jacquard grasp datasets, the accuracy rates reached 97.9% and 94.7% respectively, and the time required to process RGB-D images was 30ms. Compared with other methods, this method improves the accuracy and time efficiency, and the experiment verifies the feasibility and effectiveness of this method.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"41 8","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187205","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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