Pub Date : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011696
Hongxu Wang, Jinsheng Guo, Ziran Liu, T. Lin, Chengfei Yue, Xibin Cao
Dynamic modeling is the key technology in studying multi-arm space robots with variable topology. The difficulty lies in establishing the transformation from one topology to the other one. In this paper, typical configurations applied in orbit manipulation are demonstrated and the corresponding dynamic model are built based on spatial operator algebra(SOA). Then a general topological transformation method is proposed via factored serial topological variation. Finally, listed dynamic model of the configuration verifies the transformation result.
{"title":"Typical Topology Variation and Dynamic Transformation Method for Multi-arm Space Robot","authors":"Hongxu Wang, Jinsheng Guo, Ziran Liu, T. Lin, Chengfei Yue, Xibin Cao","doi":"10.1109/ROBIO55434.2022.10011696","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011696","url":null,"abstract":"Dynamic modeling is the key technology in studying multi-arm space robots with variable topology. The difficulty lies in establishing the transformation from one topology to the other one. In this paper, typical configurations applied in orbit manipulation are demonstrated and the corresponding dynamic model are built based on spatial operator algebra(SOA). Then a general topological transformation method is proposed via factored serial topological variation. Finally, listed dynamic model of the configuration verifies the transformation result.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114848303","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011758
Guang-Xing Liu, Wenyu Li, Fen Duan
Modern imaging modalities from airborne or space platforms generate a large amount of remote sensing images, which places a burden on storage and transmission. These remote sensing images contain lots of ground targets which cannot tolerate fidelity loss in many fields. In this paper, a novel lossless compression method named Decomposed Soft Compression is proposed which takes advantage of rich details in images. The proposed method exploits image redundancy through integer wavelet transform. Then the decomposed images are encoded with shape-based encoder. Transformation on image layers can increase the sparsity and improve the compression ratio. Ex-periments on large-scale remote sensing image datasets show that the proposed method achieves up to 17.1 % improvement in compression ratio compared with JPEG 2000.
{"title":"Decomposed Soft Compression for Remote Sensing Image","authors":"Guang-Xing Liu, Wenyu Li, Fen Duan","doi":"10.1109/ROBIO55434.2022.10011758","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011758","url":null,"abstract":"Modern imaging modalities from airborne or space platforms generate a large amount of remote sensing images, which places a burden on storage and transmission. These remote sensing images contain lots of ground targets which cannot tolerate fidelity loss in many fields. In this paper, a novel lossless compression method named Decomposed Soft Compression is proposed which takes advantage of rich details in images. The proposed method exploits image redundancy through integer wavelet transform. Then the decomposed images are encoded with shape-based encoder. Transformation on image layers can increase the sparsity and improve the compression ratio. Ex-periments on large-scale remote sensing image datasets show that the proposed method achieves up to 17.1 % improvement in compression ratio compared with JPEG 2000.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116859852","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}
The traditional dual manipulator control systems have not only complex motion coupling problems, but also larger computational burden, and hence it is difficult to meet the requirements of intelligent assembly. In this paper, based on multi-agent reinforcement learning theory, Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is investigated in the collaborative assembly shaft slot assembly via dual manipulator system. For the collaborative shaft slot assembly in the dual manipulator system, sparse rewards in traditional multi-agent reinforcement learning often exist because of the long sequence decision-making problem. For the above problems, this paper considers the influence of the decision-making of a single manipulator on the overall task rewards when the overall rewards of multi -agent reinforcement learning are designed. In the proposed algorithm, by calculating the difference before and after the state of each manipulator, and applying the difference as the internal state excitation to the overall task rewards, the traditional reward function of multi-agent reinforcement learning is improved. In order to verify the designed algorithm, the dual manipulator shaft slot assembly system and test scenario are established on the CoppeliaSim simulation platform. Simulation results show that the success rate of the shaft slot assembly via the improved MADDPG algorithm is about 83 % *
{"title":"Dual manipulator collaborative shaft slot assembly via MADDPG","authors":"Junying Yao, Xiaojuan Wang, Renqiang Li, Wenxiao Wang, X. Ping, Yongkui Liu","doi":"10.1109/ROBIO55434.2022.10011768","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011768","url":null,"abstract":"The traditional dual manipulator control systems have not only complex motion coupling problems, but also larger computational burden, and hence it is difficult to meet the requirements of intelligent assembly. In this paper, based on multi-agent reinforcement learning theory, Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is investigated in the collaborative assembly shaft slot assembly via dual manipulator system. For the collaborative shaft slot assembly in the dual manipulator system, sparse rewards in traditional multi-agent reinforcement learning often exist because of the long sequence decision-making problem. For the above problems, this paper considers the influence of the decision-making of a single manipulator on the overall task rewards when the overall rewards of multi -agent reinforcement learning are designed. In the proposed algorithm, by calculating the difference before and after the state of each manipulator, and applying the difference as the internal state excitation to the overall task rewards, the traditional reward function of multi-agent reinforcement learning is improved. In order to verify the designed algorithm, the dual manipulator shaft slot assembly system and test scenario are established on the CoppeliaSim simulation platform. Simulation results show that the success rate of the shaft slot assembly via the improved MADDPG algorithm is about 83 % *","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"318 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115026022","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011899
Jun Zhao, Le Chen, Jinhao Li, Yuliang Zhao
Sea ice detection is essential to ensure the safe navigation of ships in mid- and high-latitude ice areas. In the face of complex sea ice information, how to use the sea ice images by shipboard cameras to comprehensively, accurately and efficiently identify four types of sea ice information (Ice skin, Nile ice, Grey ice and White ice)and two kinds of sea ice background information (sea water and sky), it remains a major challenge. This study proposes an automatic semantic segmentation method for sea ice images, which first uses Rsenet50 as well as Vgg-16 network to pre-train the model and improve the network training efficiency. Then modifications to U-Net network, improvement of the coding phase of the U-Net by introducing Vgg-16 and the residual structure, construction of the new network RU-Net and VU-Net. Compared with traditional classification methods, the experimental results show that the network can accurately identify all sea ice information in sea ice images. In particular, multi-scale sea ice types can be identified in real time, greatly improving the efficiency and accuracy of the identification of sea ice types. The MIoU values were 0.73 and 0.87 and the MPA values were 0.87 and 0.94 respectively.
{"title":"Semantic Segmentation of Sea Ice Based on U-net Network Modification","authors":"Jun Zhao, Le Chen, Jinhao Li, Yuliang Zhao","doi":"10.1109/ROBIO55434.2022.10011899","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011899","url":null,"abstract":"Sea ice detection is essential to ensure the safe navigation of ships in mid- and high-latitude ice areas. In the face of complex sea ice information, how to use the sea ice images by shipboard cameras to comprehensively, accurately and efficiently identify four types of sea ice information (Ice skin, Nile ice, Grey ice and White ice)and two kinds of sea ice background information (sea water and sky), it remains a major challenge. This study proposes an automatic semantic segmentation method for sea ice images, which first uses Rsenet50 as well as Vgg-16 network to pre-train the model and improve the network training efficiency. Then modifications to U-Net network, improvement of the coding phase of the U-Net by introducing Vgg-16 and the residual structure, construction of the new network RU-Net and VU-Net. Compared with traditional classification methods, the experimental results show that the network can accurately identify all sea ice information in sea ice images. In particular, multi-scale sea ice types can be identified in real time, greatly improving the efficiency and accuracy of the identification of sea ice types. The MIoU values were 0.73 and 0.87 and the MPA values were 0.87 and 0.94 respectively.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115021565","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011727
Chenglin Yang, Zihao Chai, Xiaoxiao Yang, Hanyang Zhuang, Ming Yang
The SLAM system, which uses 3D LiDAR as the only sensor, is prone to degradation when facing a scenario with sparse structure and fewer constraints. It cannot solve the robot pose based on limited LiDAR constraint information, which leads to the localization failure and mapping failure of the SLAM system. Due to the limitations of LiDAR, it is difficult to only rely on the point cloud data provided by LiDAR to solve the problem of localization and mapping of degraded scenarios. Currently, the mainstream is to provide additional information through multi-sensor fusion and other schemes to restrict and correct the system's attitude. In the multi-source fusion system, it is still essential to determine the information reliability of each sensor source in different directions. Hence, the recognition of the degradation scenario has significant research value. In this paper, three schemes, geometric information, constraint distur-bance, and residual disturbance, are designed to quantitatively identify the degradation state of the system and estimate the degradation direction. Through experimental verification, the proposed schemes have a favorable recognition effect in the degradation scenario of the simulation environment and real environment.
{"title":"Recognition of Degradation Scenarios for LiDAR SLAM Applications","authors":"Chenglin Yang, Zihao Chai, Xiaoxiao Yang, Hanyang Zhuang, Ming Yang","doi":"10.1109/ROBIO55434.2022.10011727","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011727","url":null,"abstract":"The SLAM system, which uses 3D LiDAR as the only sensor, is prone to degradation when facing a scenario with sparse structure and fewer constraints. It cannot solve the robot pose based on limited LiDAR constraint information, which leads to the localization failure and mapping failure of the SLAM system. Due to the limitations of LiDAR, it is difficult to only rely on the point cloud data provided by LiDAR to solve the problem of localization and mapping of degraded scenarios. Currently, the mainstream is to provide additional information through multi-sensor fusion and other schemes to restrict and correct the system's attitude. In the multi-source fusion system, it is still essential to determine the information reliability of each sensor source in different directions. Hence, the recognition of the degradation scenario has significant research value. In this paper, three schemes, geometric information, constraint distur-bance, and residual disturbance, are designed to quantitatively identify the degradation state of the system and estimate the degradation direction. Through experimental verification, the proposed schemes have a favorable recognition effect in the degradation scenario of the simulation environment and real environment.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121142959","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011789
Yichun Wu, Qiuyi Gu, Jincheng Yu, Guangjun Ge, Jian Wang, Q. Liao, Chun Zhang, Yu Wang
Collaborative exploration in an unknown environ-ment is an essential task for mobile robotic systems. Without external positioning, multi-robot mapping methods have relied on the transfer of place descriptors and sensor data for relative pose estimation, which is not feasible in communication-limited environments. In addition, existing frontier-based exploration strategies are mostly designed for occupancy grid maps, thus failing to use surface information of obstacles in complex three-dimensional scenes. To address these limitations, we utilize Gaussian Mixture Model (GMM) as the map form for both mapping and exploration. We extend our previous mapping work to exploration setting by introducing MR-GMMExplore, a Multi-Robot GMM-based Exploration system in which robots transfer GMM submaps to reduce data transmission and perform exploration directly using the generated GMM map. Specifically, we propose a GMM spatial information extraction strategy that efficiently extracts obstacle probability information from GMM submaps. Then we present a goal selection method that allows robots to explore different areas, and a GMM-based local planner that realizes local planning using GMM maps instead of converting them into grid maps. Simulation results show that the transmission of GMM submaps reduces approximately 96% communication load compared with point clouds and our mean-based extraction strategy is 4 times faster than the traversal-based one. We also conduct comparative experiments to demonstrate the effectiveness of our approach in reducing backtracking paths and enhancing cooperation. MR-GMMExplore is published as an open-source ROS package at https://github.com/efc-robot/gmm_explore.
{"title":"MR-GMMExplore: Multi-Robot Exploration System in Unknown Environments based on Gaussian Mixture Model","authors":"Yichun Wu, Qiuyi Gu, Jincheng Yu, Guangjun Ge, Jian Wang, Q. Liao, Chun Zhang, Yu Wang","doi":"10.1109/ROBIO55434.2022.10011789","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011789","url":null,"abstract":"Collaborative exploration in an unknown environ-ment is an essential task for mobile robotic systems. Without external positioning, multi-robot mapping methods have relied on the transfer of place descriptors and sensor data for relative pose estimation, which is not feasible in communication-limited environments. In addition, existing frontier-based exploration strategies are mostly designed for occupancy grid maps, thus failing to use surface information of obstacles in complex three-dimensional scenes. To address these limitations, we utilize Gaussian Mixture Model (GMM) as the map form for both mapping and exploration. We extend our previous mapping work to exploration setting by introducing MR-GMMExplore, a Multi-Robot GMM-based Exploration system in which robots transfer GMM submaps to reduce data transmission and perform exploration directly using the generated GMM map. Specifically, we propose a GMM spatial information extraction strategy that efficiently extracts obstacle probability information from GMM submaps. Then we present a goal selection method that allows robots to explore different areas, and a GMM-based local planner that realizes local planning using GMM maps instead of converting them into grid maps. Simulation results show that the transmission of GMM submaps reduces approximately 96% communication load compared with point clouds and our mean-based extraction strategy is 4 times faster than the traversal-based one. We also conduct comparative experiments to demonstrate the effectiveness of our approach in reducing backtracking paths and enhancing cooperation. MR-GMMExplore is published as an open-source ROS package at https://github.com/efc-robot/gmm_explore.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121504453","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10012011
Yongxiong Xiao, Shiqiang Zhu, Wei Song, Minhong Wan, J. Gu, Te Li
The interference-plus-noise covariance matrix (INCM) is essential in improving an acoustic beamformer's interference and noise attenuation performance. In practical implementation, INCM reconstruction is required to remove the signal of interest (SOI) components from the sample covariance matrix. However, some of the interference and noise components are inevitably removed during the INCM reconstruction process to avoid distortion of the desired speech, which deteriorates the interference and noise attenuation performance of the beamformer. This paper proposes constructing an INCM with as much information on the interferences and noise as possible by adding covariance matrices of the spherically diffuse noise, background noise, and interferences. The final INCM is reconstructed by using the principal eigenvector and definition of INCM. The beamformer's weight coefficients are computed by the linearly constrained minimum variance (LCMV) formulation. The proposed method is validated by experiments using a circular microphone array mounted on a tour robot in an exhibition hall. The results show that the proposed beamformer improves the robustness of automatic speech recognition and the performance of robot audition.
{"title":"Acoustic Beamforming via Interference-Plus-Noise Covariance Matrix Construction for Interferences and Noise Attenuation","authors":"Yongxiong Xiao, Shiqiang Zhu, Wei Song, Minhong Wan, J. Gu, Te Li","doi":"10.1109/ROBIO55434.2022.10012011","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10012011","url":null,"abstract":"The interference-plus-noise covariance matrix (INCM) is essential in improving an acoustic beamformer's interference and noise attenuation performance. In practical implementation, INCM reconstruction is required to remove the signal of interest (SOI) components from the sample covariance matrix. However, some of the interference and noise components are inevitably removed during the INCM reconstruction process to avoid distortion of the desired speech, which deteriorates the interference and noise attenuation performance of the beamformer. This paper proposes constructing an INCM with as much information on the interferences and noise as possible by adding covariance matrices of the spherically diffuse noise, background noise, and interferences. The final INCM is reconstructed by using the principal eigenvector and definition of INCM. The beamformer's weight coefficients are computed by the linearly constrained minimum variance (LCMV) formulation. The proposed method is validated by experiments using a circular microphone array mounted on a tour robot in an exhibition hall. The results show that the proposed beamformer improves the robustness of automatic speech recognition and the performance of robot audition.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123315047","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011856
Sheng Bi, Chuanhong Guo, Wenxing Yang, Geoge Zhang, Jiangcheng Chen, Yu Wang, I. Elhajj, Roy Vellaisamy
ROS is widely used in robot development. However, ROS is mainly based on LAN. So, an internet software framework needs to be designed based on ROS for telerobot development. An internet software framework based on ROS is proposed in this paper, including network communication system and robot internet software system. The network communication system implements a latency-optimized hierarchical data transmission protocol suitable for internet teleoperation and remote control, while the robot internet software system implements the internet teleoperation and remote control based on ROS. Finally, the experiment verifies the effectiveness of the system in data transmission and remote human-computer interaction under the internet environment.
{"title":"A software framework for internet telerobot based on ROS","authors":"Sheng Bi, Chuanhong Guo, Wenxing Yang, Geoge Zhang, Jiangcheng Chen, Yu Wang, I. Elhajj, Roy Vellaisamy","doi":"10.1109/ROBIO55434.2022.10011856","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011856","url":null,"abstract":"ROS is widely used in robot development. However, ROS is mainly based on LAN. So, an internet software framework needs to be designed based on ROS for telerobot development. An internet software framework based on ROS is proposed in this paper, including network communication system and robot internet software system. The network communication system implements a latency-optimized hierarchical data transmission protocol suitable for internet teleoperation and remote control, while the robot internet software system implements the internet teleoperation and remote control based on ROS. Finally, the experiment verifies the effectiveness of the system in data transmission and remote human-computer interaction under the internet environment.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123579790","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011708
Yaohui Xu, Junzhe Hu, Jinhua Song, Fengran Xie, Qiyang Zuo, Kai He
Animals living around water and marine environments have undergone a long evolutionary process and have developed a variety of propellers to enable rapid movement through the water. Loons, a kind of diving birds, use deformable, propulsion-generating feet to move through highly viscous fluid environments, and rely on the strong propulsion generated by the feet of this structure to enable them to dive to 70 meters and hunt fish in the water. Inspired by loons, a novel propeller for swimming robot was designed. A linkage with non-linear compliant oscillatory paddles mimicking loon's propelling mechanics, for thrust-efficient and agile locomotion, was firstly proposed. Arming to greater thrust and miniaturization, the method connecting linkage and the paddles is proposed which enables all the paddles oscillator synchronously to produce more thrust in the power stroke. Meanwhile, each compliant paddle, featured one-sided jointed limits, could create asymmetric gait cycle that avoids greater resistance in the recovery stroke. Furthermore, to analyze and evaluate the movement as well as the deformation and propelling force, the blade element theory was utilized to describe the dynamic model of the proposed propellers. Finally, experiments were carried out to verify the design and dynamic model. Overall, this paper offers a feasible and pragmatic design for biomimetic robot with multiple propellers synchronous propelling.
{"title":"A Novel Multiple Synchronous Compliant and Passive Propeller Inspired by Loons for Swimming Robot","authors":"Yaohui Xu, Junzhe Hu, Jinhua Song, Fengran Xie, Qiyang Zuo, Kai He","doi":"10.1109/ROBIO55434.2022.10011708","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011708","url":null,"abstract":"Animals living around water and marine environments have undergone a long evolutionary process and have developed a variety of propellers to enable rapid movement through the water. Loons, a kind of diving birds, use deformable, propulsion-generating feet to move through highly viscous fluid environments, and rely on the strong propulsion generated by the feet of this structure to enable them to dive to 70 meters and hunt fish in the water. Inspired by loons, a novel propeller for swimming robot was designed. A linkage with non-linear compliant oscillatory paddles mimicking loon's propelling mechanics, for thrust-efficient and agile locomotion, was firstly proposed. Arming to greater thrust and miniaturization, the method connecting linkage and the paddles is proposed which enables all the paddles oscillator synchronously to produce more thrust in the power stroke. Meanwhile, each compliant paddle, featured one-sided jointed limits, could create asymmetric gait cycle that avoids greater resistance in the recovery stroke. Furthermore, to analyze and evaluate the movement as well as the deformation and propelling force, the blade element theory was utilized to describe the dynamic model of the proposed propellers. Finally, experiments were carried out to verify the design and dynamic model. Overall, this paper offers a feasible and pragmatic design for biomimetic robot with multiple propellers synchronous propelling.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123945787","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 : 2022-12-05DOI: 10.1109/ROBIO55434.2022.10011711
Lixi Chen, Wei Fang, Zhan Teng
Limitations exist in the application of surgical robots in clinical practice such as doctors' limited field of vision, lack of depth information, and the need to constantly switch the field of vision in the process of surgery, which affects the efficiency of surgery. In this paper, research on stereo 3D display for augmented reality (AR) surgical navigation is carried out to address the issues, which combines the technology of AR to overlay the virtual 3D model with the actual image of the operation area, providing doctors and surgical assistants with a more intuitive display method of the lesion location of patients during the operation. The stereo 3D display is presented in detail, including the theoretical research, the algorithm model, the AR effect test, and the positioning error analysis. The simulation and experiments are conducted to evaluate the performance of the stereo 3D display, which verified the practicability and effectiveness of the system and showed that the system can correctly realize pose estimation, virtual model projection, and presentation of AR effect.
{"title":"Research on Stereo 3D Display for Augmented Reality Surgical Navigation","authors":"Lixi Chen, Wei Fang, Zhan Teng","doi":"10.1109/ROBIO55434.2022.10011711","DOIUrl":"https://doi.org/10.1109/ROBIO55434.2022.10011711","url":null,"abstract":"Limitations exist in the application of surgical robots in clinical practice such as doctors' limited field of vision, lack of depth information, and the need to constantly switch the field of vision in the process of surgery, which affects the efficiency of surgery. In this paper, research on stereo 3D display for augmented reality (AR) surgical navigation is carried out to address the issues, which combines the technology of AR to overlay the virtual 3D model with the actual image of the operation area, providing doctors and surgical assistants with a more intuitive display method of the lesion location of patients during the operation. The stereo 3D display is presented in detail, including the theoretical research, the algorithm model, the AR effect test, and the positioning error analysis. The simulation and experiments are conducted to evaluate the performance of the stereo 3D display, which verified the practicability and effectiveness of the system and showed that the system can correctly realize pose estimation, virtual model projection, and presentation of AR effect.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124460837","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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