Energy harvesting wireless sensor nodes collect energy in a nonlinear dynamic change, resulting in low ability to dynamically match the collected and consumed energy of the node in the process of maintaining energy neutral operation (ENO).To address this problem, the concept of battery ENO (BENO) is proposed by analyzing the battery energy buffer characteristics, and the dual-actor critic energy harvesting wireless sensor node adaptive energy management (DAC) method is proposed based on BENO. The method designs a dual-actor critic structure, senses ENO through the battery energy neutral value, and dynamically adjusts the duty cycle based on this value, in order to achieve the purpose of improving the ability of dynamically matching the collected energy with the consumed energy. The experiments are carried out on three datasets with different energy harvesting capabilities, and compared and analyzed with three classical algorithms, RLman, AQL and FQL. The experimental results show that compared with the other three classical algorithms, DAC sacrifices a small amount of duty cycle, but effectively improves the stability of battery energy, and improves the energy utilization and ENO performance. The BENO concept and the DAC methodology can provide guidance and references for the research of energy management in energy-harvesting wireless sensor nodes.
{"title":"Dual-Actor Critic Adaptive Energy Management Method for EH-WSN Based on Battery Energy Neutral Operation","authors":"Shuhua Yuan;Yongqi Ge;Xin Chen;Yalin Wang;Rui Liu;Jintao Gao","doi":"10.1109/JSEN.2024.3472089","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3472089","url":null,"abstract":"Energy harvesting wireless sensor nodes collect energy in a nonlinear dynamic change, resulting in low ability to dynamically match the collected and consumed energy of the node in the process of maintaining energy neutral operation (ENO).To address this problem, the concept of battery ENO (BENO) is proposed by analyzing the battery energy buffer characteristics, and the dual-actor critic energy harvesting wireless sensor node adaptive energy management (DAC) method is proposed based on BENO. The method designs a dual-actor critic structure, senses ENO through the battery energy neutral value, and dynamically adjusts the duty cycle based on this value, in order to achieve the purpose of improving the ability of dynamically matching the collected energy with the consumed energy. The experiments are carried out on three datasets with different energy harvesting capabilities, and compared and analyzed with three classical algorithms, RLman, AQL and FQL. The experimental results show that compared with the other three classical algorithms, DAC sacrifices a small amount of duty cycle, but effectively improves the stability of battery energy, and improves the energy utilization and ENO performance. The BENO concept and the DAC methodology can provide guidance and references for the research of energy management in energy-harvesting wireless sensor nodes.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38466-38478"},"PeriodicalIF":4.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surface electromyography (sEMG) and ultrasound-based sonomyography (SMG) are established muscle activity monitoring techniques. However, both modalities require contact with the skin and are thus potentially uncomfortable and time-consuming to use. In this article, we propose a novel noncontact muscle activity monitoring approach that measures the muscle deformation signal using a frequency-modulated continuous wave (FMCW) mmWave radar which we call radiomyography (RMG). The RMG signal is a specific sequence of phase samples in the radar return, obtained through a series of operations: range bin selection, dc offset correction, arctangent demodulation, and phase unwrapping. We find that the RMG signal highly correlates with the sEMG signal across time, making RMG a reliable method for monitoring muscle activity. We also establish that our signal contains some characteristic features of the muscle deformation signal that are well known in biomechanics. Our main contribution is the proposal, development, and proof-of-concept usage of a novel noncontact muscle activity monitoring approach. This opens muscle activity monitoring up for use in rehabilitation, high-intensity contact sports analytics, performance arts, remote health monitoring, and wildlife healthcare and research. To the best of the authors’ knowledge, our approach is the first to measure the characteristic dimensional changes of muscles in vivo and without contact.
{"title":"Toward Noncontact Muscle Activity Estimation Using FMCW Radar","authors":"Kukhokuhle Tsengwa;Stephen Paine;Fred Nicolls;Yumna Albertus;Amir Patel","doi":"10.1109/JSEN.2024.3472571","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3472571","url":null,"abstract":"Surface electromyography (sEMG) and ultrasound-based sonomyography (SMG) are established muscle activity monitoring techniques. However, both modalities require contact with the skin and are thus potentially uncomfortable and time-consuming to use. In this article, we propose a novel noncontact muscle activity monitoring approach that measures the muscle deformation signal using a frequency-modulated continuous wave (FMCW) mmWave radar which we call radiomyography (RMG). The RMG signal is a specific sequence of phase samples in the radar return, obtained through a series of operations: range bin selection, dc offset correction, arctangent demodulation, and phase unwrapping. We find that the RMG signal highly correlates with the sEMG signal across time, making RMG a reliable method for monitoring muscle activity. We also establish that our signal contains some characteristic features of the muscle deformation signal that are well known in biomechanics. Our main contribution is the proposal, development, and proof-of-concept usage of a novel noncontact muscle activity monitoring approach. This opens muscle activity monitoring up for use in rehabilitation, high-intensity contact sports analytics, performance arts, remote health monitoring, and wildlife healthcare and research. To the best of the authors’ knowledge, our approach is the first to measure the characteristic dimensional changes of muscles in vivo and without contact.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"37595-37606"},"PeriodicalIF":4.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-08DOI: 10.1109/JSEN.2024.3472072
Penghui Zhao;Haiwen Yuan;Yingyi Liu;Jianxun Lv;Yuxin Deng
Audible noise is crucial in designing and constructing high-voltage transmission lines. However, when measuring the audible noise of power lines, it is susceptible to interference from other noise sources in the external environment, posing significant challenges to data analysis and processing. To address the issue, we propose a method for measuring audible noise using a microphone array based on beamforming. We design filters using the FIR wideband beamforming algorithm and apply them to a single-direction incidence model. Filters designed using the phase iteration method are applied to a multidirection incidence model. Factors affecting beamformer accuracy and solutions have also been discussed. Simulation results demonstrate that both filters effectively suppress interference signals from other directions while preserving the desired direction signal. Experiments in a corona cage show that the beamforming filters can suppress external interference noise by more than 10.2 dB, validating the proposed algorithms and providing guidance to design high-voltage transmission lines in the future.
可听噪声对设计和建造高压输电线路至关重要。然而，在测量输电线路的可听噪声时，它很容易受到外部环境中其他噪声源的干扰，给数据分析和处理带来巨大挑战。为了解决这个问题，我们提出了一种基于波束成形的麦克风阵列测量可听噪声的方法。我们使用 FIR 宽带波束成形算法设计滤波器，并将其应用于单向入射模型。使用相位迭代法设计的滤波器适用于多方向入射模型。此外，还讨论了影响波束成形器精度和解决方案的因素。仿真结果表明，这两种滤波器都能有效抑制来自其他方向的干扰信号，同时保留所需的方向信号。电晕笼中的实验表明，波束成形滤波器能抑制外部干扰噪声 10.2 dB 以上，从而验证了所提出的算法，并为今后设计高压输电线路提供了指导。
{"title":"Audible Noise Measurement of High-Voltage Transmission Lines Using Beamforming","authors":"Penghui Zhao;Haiwen Yuan;Yingyi Liu;Jianxun Lv;Yuxin Deng","doi":"10.1109/JSEN.2024.3472072","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3472072","url":null,"abstract":"Audible noise is crucial in designing and constructing high-voltage transmission lines. However, when measuring the audible noise of power lines, it is susceptible to interference from other noise sources in the external environment, posing significant challenges to data analysis and processing. To address the issue, we propose a method for measuring audible noise using a microphone array based on beamforming. We design filters using the FIR wideband beamforming algorithm and apply them to a single-direction incidence model. Filters designed using the phase iteration method are applied to a multidirection incidence model. Factors affecting beamformer accuracy and solutions have also been discussed. Simulation results demonstrate that both filters effectively suppress interference signals from other directions while preserving the desired direction signal. Experiments in a corona cage show that the beamforming filters can suppress external interference noise by more than 10.2 dB, validating the proposed algorithms and providing guidance to design high-voltage transmission lines in the future.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"37575-37585"},"PeriodicalIF":4.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-08DOI: 10.1109/JSEN.2024.3472076
Zhu Sun;Yin-Li Jin;Yu-Jie Zhang;Wen-Peng Xu;Li Li
Accurate estimation of the ambient temperature of mountain freeways enables freeway management agencies to provide weather-related information to drivers. This article proposed an image-based data-driven method, namely the visual temperature estimation network (VTENet), to estimate freeway ambient temperature based on images captured by roadside cameras. The VTENet had a convolutional neural network (CNN) architecture to extract temperature-related image features, and two extra networks to capture space-time information on data collection and time-series image features. The VTENet was trained and tested based on a self-established dataset collected at a mountain freeway. The results showed that the VTENet can estimate freeway ambient temperature with high accuracy. The model gives a more accurate temperature estimation with data collected from 10 to 11 A.M. and 2 to 3 P.M. than other periods. It also performed better using four-day or five-day sequence images than other data inputs.
{"title":"Ambient Temperature Estimation of Mountain Freeways Based on Roadside Camera Images","authors":"Zhu Sun;Yin-Li Jin;Yu-Jie Zhang;Wen-Peng Xu;Li Li","doi":"10.1109/JSEN.2024.3472076","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3472076","url":null,"abstract":"Accurate estimation of the ambient temperature of mountain freeways enables freeway management agencies to provide weather-related information to drivers. This article proposed an image-based data-driven method, namely the visual temperature estimation network (VTENet), to estimate freeway ambient temperature based on images captured by roadside cameras. The VTENet had a convolutional neural network (CNN) architecture to extract temperature-related image features, and two extra networks to capture space-time information on data collection and time-series image features. The VTENet was trained and tested based on a self-established dataset collected at a mountain freeway. The results showed that the VTENet can estimate freeway ambient temperature with high accuracy. The model gives a more accurate temperature estimation with data collected from 10 to 11 A.M. and 2 to 3 P.M. than other periods. It also performed better using four-day or five-day sequence images than other data inputs.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38453-38465"},"PeriodicalIF":4.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Energy consumption has been the focus of routing protocols in underwater acoustic sensor networks (UASNs), and many cluster-based routing protocols have been proposed to optimize energy consumption. However, there is the “hotspot” problem resulting from frequent data forwarding by cluster heads (CHs) and energy inefficiency caused by the transmission of data packets from shallow water to deep water. Therefore, we propose an energy-balanced routing protocol with nonuniform clustering (ERNC) to balance energy consumption and improve data transmission efficiency. First, without accurate 3-D localization, nodes exchange information with each other, and the combined coordinate of layer ID and hop ID is proposed to represent the node’s location information for subsequent CH selection and intercluster routing. Then, the combined coordinate, residual energy, and node density are considered comprehensively to select CHs for making their distribution uneven and equalizing the energy consumption. In the intercluster routing phase, the next hop candidate node sets with different forwarding priorities are constructed based on nodes’ coordinates to improve the network transmission efficiency. Moreover, we design the different holding times for the next-hop nodes in the same set to balance the energy consumption of CHs. The simulation results show that ERNC can effectively extend the network lifetime and improve the data transmission performance.
能耗一直是水下声学传感器网络（UASN）中路由协议的重点，许多基于簇的路由协议被提出来优化能耗。然而，由于簇头（CHs）频繁转发数据导致的 "热点 "问题，以及数据包从浅水区向深水区传输导致的能效低下问题。因此，我们提出了一种非均匀聚类的能量平衡路由协议（ERNC），以平衡能量消耗并提高数据传输效率。首先，在没有精确三维定位的情况下，节点之间相互交换信息，并提出了层 ID 和跳 ID 的组合坐标来代表节点的位置信息，用于后续的 CH 选择和簇间路由。然后，综合考虑组合坐标、剩余能量和节点密度来选择 CH，使其分布不均匀，并均衡能量消耗。在簇间路由阶段，根据节点坐标构建具有不同转发优先级的下一跳候选节点集，以提高网络传输效率。此外，我们还为同一组中的下一跳节点设计了不同的保持时间，以平衡 CHs 的能量消耗。仿真结果表明，ERNC 能有效延长网络寿命，提高数据传输性能。
{"title":"Energy-Balanced Routing Protocol With Nonuniform Clustering for Underwater Acoustic Sensors Networks","authors":"Zhigang Jin;Haoyong Li;Ying Wang;Jiawei Liang;Simeng Cheng","doi":"10.1109/JSEN.2024.3471878","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3471878","url":null,"abstract":"Energy consumption has been the focus of routing protocols in underwater acoustic sensor networks (UASNs), and many cluster-based routing protocols have been proposed to optimize energy consumption. However, there is the “hotspot” problem resulting from frequent data forwarding by cluster heads (CHs) and energy inefficiency caused by the transmission of data packets from shallow water to deep water. Therefore, we propose an energy-balanced routing protocol with nonuniform clustering (ERNC) to balance energy consumption and improve data transmission efficiency. First, without accurate 3-D localization, nodes exchange information with each other, and the combined coordinate of layer ID and hop ID is proposed to represent the node’s location information for subsequent CH selection and intercluster routing. Then, the combined coordinate, residual energy, and node density are considered comprehensively to select CHs for making their distribution uneven and equalizing the energy consumption. In the intercluster routing phase, the next hop candidate node sets with different forwarding priorities are constructed based on nodes’ coordinates to improve the network transmission efficiency. Moreover, we design the different holding times for the next-hop nodes in the same set to balance the energy consumption of CHs. The simulation results show that ERNC can effectively extend the network lifetime and improve the data transmission performance.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38082-38091"},"PeriodicalIF":4.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The micro-range curve extraction of scattering centers is significant for estimating the motion and structural parameters of space targets. The curves are often extracted from high-resolution range profile (HRRP) for its range dimension information. However, most of the existing curve extraction algorithms based on HRRPs are with the accuracy of curves limited by range resolution. Moreover, due to noise interference, it is difficult to achieve extraction under low signal-to-noise ratio (SNR). Therefore, a super-resolution micro-range extraction algorithm based on the parameter correlation between micro-range curves and micro-Doppler (m-D) curves is proposed in this article. First, a parametric curve model is constructed and a rough parameter search of model is conducted to obtain the initial range curve, which ensures the robustness and real-time performance. Second, time-frequency analysis is applied to the range bins of the curve, and the m-D curve is refined by local maxima search to further improve the accuracy. The accurate micro-range curve is then reconstructed with the absolute range acquired by a 1-D search. Finally, simulation and experiment are carried out to verify the effectiveness and superiority of the proposed algorithm, which can achieve a better accuracy when SNR is −10 dB, compared with the existing methods.
散射中心的微距曲线提取对于估计空间目标的运动和结构参数非常重要。通常从高分辨率测距剖面图（HRRP）中提取曲线，以获取其测距维度信息。然而，现有的大多数基于高分辨率测距剖面的曲线提取算法的曲线精度都受到测距分辨率的限制。此外，由于噪声干扰，在信噪比（SNR）较低的情况下很难实现提取。因此，本文提出了一种基于微距曲线和微多普勒（m-D）曲线之间参数相关性的超分辨率微距提取算法。首先，构建参数曲线模型，并对模型进行粗略参数搜索，得到初始测距曲线，保证了算法的鲁棒性和实时性。其次，对曲线的测距分段进行时频分析，并通过局部最大值搜索对 m-D 曲线进行细化，进一步提高精度。然后，利用一维搜索获得的绝对量程重建精确的微量程曲线。最后，通过仿真和实验验证了所提算法的有效性和优越性，与现有方法相比，该算法在信噪比为 -10 dB 时可以达到更高的精度。
{"title":"Super-Resolution Micro-Range Curve Extraction for Precession Cone-Shaped Targets Based on Multidimensional Information","authors":"Jing Wu;Zhiming Xu;Xiaofeng Ai;Yuqing Zheng;Qihua Wu","doi":"10.1109/JSEN.2024.3471797","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3471797","url":null,"abstract":"The micro-range curve extraction of scattering centers is significant for estimating the motion and structural parameters of space targets. The curves are often extracted from high-resolution range profile (HRRP) for its range dimension information. However, most of the existing curve extraction algorithms based on HRRPs are with the accuracy of curves limited by range resolution. Moreover, due to noise interference, it is difficult to achieve extraction under low signal-to-noise ratio (SNR). Therefore, a super-resolution micro-range extraction algorithm based on the parameter correlation between micro-range curves and micro-Doppler (m-D) curves is proposed in this article. First, a parametric curve model is constructed and a rough parameter search of model is conducted to obtain the initial range curve, which ensures the robustness and real-time performance. Second, time-frequency analysis is applied to the range bins of the curve, and the m-D curve is refined by local maxima search to further improve the accuracy. The accurate micro-range curve is then reconstructed with the absolute range acquired by a 1-D search. Finally, simulation and experiment are carried out to verify the effectiveness and superiority of the proposed algorithm, which can achieve a better accuracy when SNR is −10 dB, compared with the existing methods.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"37544-37556"},"PeriodicalIF":4.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1109/JSEN.2024.3471618
Xiong Cheng;Zhixiang Zhai;Pengfei Zhang;Yiqi Zhou;Rui Wang;Wenhua Gu;Xiaodong Huang;Daying Sun
Designing micro-electro-mechanical system (MEMS) sensors to meet specific performance requirements is essential. Traditional approaches, which rely heavily on expert knowledge and extensive finite-element simulations, are often time-consuming. Current deep learning (DL) methods in MEMS design typically focus on finding a single feasible solution, neglecting the need to generate multiple solutions simultaneously, which is critical in practical design scenarios. This article presents a methodology to address these limitations, introducing a hybrid network called the conditional variational autoencoder (VAE) and generative adversarial network (CVAE-GAN), along with a multisolution generator (G-MS). The CVAE-GAN enables high-accuracy and high-efficiency inverse design, while the G-MS, with its tailored noise updating strategy, generates multiple distinct feasible solutions for given performance criteria. This methodology has been experimentally validated on a piezoresistive MEMS accelerometer, finding the second solution in $3.60~pm ~2.46$ s, with a normalized distance of $0.75~pm ~0.19$ , improving the existing method as much as $3.63times $ and $7.19times $ , respectively. While traditional methods struggle to find more than two solutions, our G-MS can continuously output solutions according to the specified number, with the time taken to find each solution remaining nearly constant. This approach demonstrates the capability to quickly generate multiple accurate structural parameters based on desired performance, showcasing significant potential and providing valuable insights for MEMS sensor design.
{"title":"Generating Multiple Distinct Feasible Solutions for MEMS Accelerometers Using Deep Learning","authors":"Xiong Cheng;Zhixiang Zhai;Pengfei Zhang;Yiqi Zhou;Rui Wang;Wenhua Gu;Xiaodong Huang;Daying Sun","doi":"10.1109/JSEN.2024.3471618","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3471618","url":null,"abstract":"Designing micro-electro-mechanical system (MEMS) sensors to meet specific performance requirements is essential. Traditional approaches, which rely heavily on expert knowledge and extensive finite-element simulations, are often time-consuming. Current deep learning (DL) methods in MEMS design typically focus on finding a single feasible solution, neglecting the need to generate multiple solutions simultaneously, which is critical in practical design scenarios. This article presents a methodology to address these limitations, introducing a hybrid network called the conditional variational autoencoder (VAE) and generative adversarial network (CVAE-GAN), along with a multisolution generator (G-MS). The CVAE-GAN enables high-accuracy and high-efficiency inverse design, while the G-MS, with its tailored noise updating strategy, generates multiple distinct feasible solutions for given performance criteria. This methodology has been experimentally validated on a piezoresistive MEMS accelerometer, finding the second solution in \u0000<inline-formula> <tex-math>$3.60~pm ~2.46$ </tex-math></inline-formula>\u0000 s, with a normalized distance of \u0000<inline-formula> <tex-math>$0.75~pm ~0.19$ </tex-math></inline-formula>\u0000, improving the existing method as much as \u0000<inline-formula> <tex-math>$3.63times $ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>$7.19times $ </tex-math></inline-formula>\u0000, respectively. While traditional methods struggle to find more than two solutions, our G-MS can continuously output solutions according to the specified number, with the time taken to find each solution remaining nearly constant. This approach demonstrates the capability to quickly generate multiple accurate structural parameters based on desired performance, showcasing significant potential and providing valuable insights for MEMS sensor design.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38377-38386"},"PeriodicalIF":4.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1109/JSEN.2024.3471651
Yirui Zhang;Jiabo Xu;Yanni Zou;Peter X. Liu
Accurately registering point clouds is challenging due to three primary reasons: 1) it is difficult for point cloud feature descriptors to handle noise in complex scenes; 2) poorly descriptive features lead to incorrect sets of corresponding points; and 3) non-overlapping regions in the scene can adversely affect registration results. To address these issues, our approach consists of three key contributions. First, we propose a segmenting sphere region (SSR) feature descriptor that comprehensively preserves point cloud spatial coordinate information through the “sphere segmentation-furthest point preservation” operation, enabling robust registration in complex scenarios. Second, we design SSR-Net to improve the descriptiveness of SSR features, generating a soft matching matrix to estimate the correspondence between the improved features. Finally, we design an overlap region estimation module in SSR-Net, which employs attention to find the overlap region, thereby reducing the negative impact of non-overlapping regions in the soft matching matrix on registration results. We conducted comprehensive experiments on the B3R, ModelNet40, KITTI, unmanned aerial vehicle (UAV), and 3DMatch datasets, demonstrating the effectiveness of our proposed method.
{"title":"A Point Cloud Registration Method Based on Segmenting Sphere Region Feature Descriptor and Overlapping Region Matching Strategy","authors":"Yirui Zhang;Jiabo Xu;Yanni Zou;Peter X. Liu","doi":"10.1109/JSEN.2024.3471651","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3471651","url":null,"abstract":"Accurately registering point clouds is challenging due to three primary reasons: 1) it is difficult for point cloud feature descriptors to handle noise in complex scenes; 2) poorly descriptive features lead to incorrect sets of corresponding points; and 3) non-overlapping regions in the scene can adversely affect registration results. To address these issues, our approach consists of three key contributions. First, we propose a segmenting sphere region (SSR) feature descriptor that comprehensively preserves point cloud spatial coordinate information through the “sphere segmentation-furthest point preservation” operation, enabling robust registration in complex scenarios. Second, we design SSR-Net to improve the descriptiveness of SSR features, generating a soft matching matrix to estimate the correspondence between the improved features. Finally, we design an overlap region estimation module in SSR-Net, which employs attention to find the overlap region, thereby reducing the negative impact of non-overlapping regions in the soft matching matrix on registration results. We conducted comprehensive experiments on the B3R, ModelNet40, KITTI, unmanned aerial vehicle (UAV), and 3DMatch datasets, demonstrating the effectiveness of our proposed method.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38387-38401"},"PeriodicalIF":4.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1109/JSEN.2024.3470817
Jianfeng Lin;Chenkun Qi;Yan Hu;Feng Gao
The performance of actuator in nanopositioning system is significant to guarantee the rapidity and accuracy of closed-loop positioning control. However, the current actuators exhibit deficiencies including limited driving force and low accuracy because of the conflicting relationship between stiffness and resolution. In this article, a novel heavy payload high-resolution actuator (HPHRA) system is designed based on hydraulic transmission principle for nanopositioning robotic application. To achieve an accurate model, a compensatory Hammerstein model recognition strategy is proposed to capture the internal different physical characteristics, which is named compensatory nonlinear linear model (CNLM). The linear dynamics is captured by a linear transfer function, and the nonlinear dynamics is captured by a hysteresis PI model with several backlash operators. The residuals between nonlinear linear Hammerstein model and actual position, which is caused by external load, are compensated by a neural network. The CNLM recognition strategy is developed based on the regularized least square algorithm, singular value decomposition, and gradient descent algorithm. Experimental evidence on the HPHRA confirms the efficacy of the proposed CNLM method. The nanopositioning control in a 12-DOF macro–micro double parallel (12-MMDPR) robot under heavy load provides evidence of the HPHRA, CLNM strategy, and composite controller.
{"title":"A Novel Heavy Payload High-Resolution Actuator System: Design, Modeling, and Experiments","authors":"Jianfeng Lin;Chenkun Qi;Yan Hu;Feng Gao","doi":"10.1109/JSEN.2024.3470817","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3470817","url":null,"abstract":"The performance of actuator in nanopositioning system is significant to guarantee the rapidity and accuracy of closed-loop positioning control. However, the current actuators exhibit deficiencies including limited driving force and low accuracy because of the conflicting relationship between stiffness and resolution. In this article, a novel heavy payload high-resolution actuator (HPHRA) system is designed based on hydraulic transmission principle for nanopositioning robotic application. To achieve an accurate model, a compensatory Hammerstein model recognition strategy is proposed to capture the internal different physical characteristics, which is named compensatory nonlinear linear model (CNLM). The linear dynamics is captured by a linear transfer function, and the nonlinear dynamics is captured by a hysteresis PI model with several backlash operators. The residuals between nonlinear linear Hammerstein model and actual position, which is caused by external load, are compensated by a neural network. The CNLM recognition strategy is developed based on the regularized least square algorithm, singular value decomposition, and gradient descent algorithm. Experimental evidence on the HPHRA confirms the efficacy of the proposed CNLM method. The nanopositioning control in a 12-DOF macro–micro double parallel (12-MMDPR) robot under heavy load provides evidence of the HPHRA, CLNM strategy, and composite controller.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"37031-37041"},"PeriodicalIF":4.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1109/JSEN.2024.3471812
Xuyang Zhang;Tianqi Yang;Dandan Zhang;Nathan F. Lepora
Manipulating fragile objects in environments such as homes and factories requires stable and gentle grasping along with precise and safe placement. Compared to traditional rigid grippers, the use of soft grippers reduces the control complexity and the risk of damaging objects. However, it is challenging to integrate camera-based optical tactile sensing into a soft gripper without compromising the flexibility and adaptability of the fingers, while also ensuring that the precision of tactile perception remains unaffected by passive deformations of the soft structure during object contact. In this article, we demonstrate a modular soft two-fingered gripper with a 3-D-printed optical tactile sensor (the TacTip) integrated into the palm. We propose a soft-grasping strategy that includes three functions: light contact detection, grasp pose adjustment, and loss-of-contact detection so that objects of different shapes and sizes can be grasped stably and placed precisely, which we test with both artificial and household objects. By sequentially implementing these three functions, the grasp success rate progressively improves from 45% without any functions, to 59% with light contact detection, 90% with grasp pose adjustment, and 97% with loss-of-contact detection, achieving a submillimeter placement precision. Overall, this work demonstrates the feasibility and utility of integrating optical tactile sensors into the palm of a soft gripper and of applicability to various types of soft manipulators. The proposed grasping strategy has potential applications in areas such as fragile product processing and home assistance.
{"title":"TacPalm: A Soft Gripper With a Biomimetic Optical Tactile Palm for Stable Precise Grasping","authors":"Xuyang Zhang;Tianqi Yang;Dandan Zhang;Nathan F. Lepora","doi":"10.1109/JSEN.2024.3471812","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3471812","url":null,"abstract":"Manipulating fragile objects in environments such as homes and factories requires stable and gentle grasping along with precise and safe placement. Compared to traditional rigid grippers, the use of soft grippers reduces the control complexity and the risk of damaging objects. However, it is challenging to integrate camera-based optical tactile sensing into a soft gripper without compromising the flexibility and adaptability of the fingers, while also ensuring that the precision of tactile perception remains unaffected by passive deformations of the soft structure during object contact. In this article, we demonstrate a modular soft two-fingered gripper with a 3-D-printed optical tactile sensor (the TacTip) integrated into the palm. We propose a soft-grasping strategy that includes three functions: light contact detection, grasp pose adjustment, and loss-of-contact detection so that objects of different shapes and sizes can be grasped stably and placed precisely, which we test with both artificial and household objects. By sequentially implementing these three functions, the grasp success rate progressively improves from 45% without any functions, to 59% with light contact detection, 90% with grasp pose adjustment, and 97% with loss-of-contact detection, achieving a submillimeter placement precision. Overall, this work demonstrates the feasibility and utility of integrating optical tactile sensors into the palm of a soft gripper and of applicability to various types of soft manipulators. The proposed grasping strategy has potential applications in areas such as fragile product processing and home assistance.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38402-38416"},"PeriodicalIF":4.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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