Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536184
Cheng Wang, Jianqiang Li, Jie Chen, Heng Zhang, Li Wang, Zun Liu
Chronic respiratory diseases are one of the leading causes of death in the world. Respiratory sounds are an important indicator to diagnose the most diseases related to respiratory system. Many recent works have focused on the analysis of adventitious sounds. Unfortunately, these approaches cannot analyze respiratory sounds in real time during auscultation and lack an easily trusted model by doctors. In this paper, we propose a novel respiratory sound analysis framework with interpretable ensemble knowledge distillation. In our work, multiple teacher models will be trained to learn lung sounds from different sources, and then they will apply the learned knowledge to guide the student model training through knowledge distillation to make our model more powerful in predicting accuracy and efficiency. Meanwhile, our model is interpretable and reliable, and its process of prediction will be approximated by the decision tree regularization. Experiments demonstrate the effectiveness of our method on the respiratory sound database.
{"title":"Interpretable Respiratory Sound Analysis with Ensemble Knowledge Distillation","authors":"Cheng Wang, Jianqiang Li, Jie Chen, Heng Zhang, Li Wang, Zun Liu","doi":"10.1109/ICARM52023.2021.9536184","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536184","url":null,"abstract":"Chronic respiratory diseases are one of the leading causes of death in the world. Respiratory sounds are an important indicator to diagnose the most diseases related to respiratory system. Many recent works have focused on the analysis of adventitious sounds. Unfortunately, these approaches cannot analyze respiratory sounds in real time during auscultation and lack an easily trusted model by doctors. In this paper, we propose a novel respiratory sound analysis framework with interpretable ensemble knowledge distillation. In our work, multiple teacher models will be trained to learn lung sounds from different sources, and then they will apply the learned knowledge to guide the student model training through knowledge distillation to make our model more powerful in predicting accuracy and efficiency. Meanwhile, our model is interpretable and reliable, and its process of prediction will be approximated by the decision tree regularization. Experiments demonstrate the effectiveness of our method on the respiratory sound database.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131539268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536078
Lianjie Guo, Hu Shi, Qichun Song, Zhaoying Liu
Robot-assisted technology for minimally invasive surgery (MIS) can improve the quality of surgery and help surgeons carry out surgery more easily. The remote center of motion (RCM) mechanism with multiple degrees of freedom (DoFs) is one of the key parts of the MIS robot. A linear motion unit is usually used to realize the translation of the surgical tool along its axis in existing RCM mechanisms, which occupies a large space above the patient’s body and is prone to interference. Based on the double parallelogram mechanism, an RCM mechanism is proposed, which can realize pitch and translation motion of the surgical tool. The geometrical modeling is introduced first to prove that there is a remote center of the mechanism during its movement. Then, the inverse kinematics is analyzed on the basis of geometrical modeling of the mechanism. Furthermore, the singularity, Jacobian matrix and the kinematic performance of the mechanism are analyzed, and the workspace is verified with the kinematics equation. Finally, a prototype based on the proposed RCM mechanism was built to test its function. The results indicate that the remote center motion can be realized by this mechanism, and it can be used to develop an MIS manipulator.
{"title":"Kinematic Design of a 2DoFs Remote Center of Motion Mechanism for Minimally Invasive Surgical Robot","authors":"Lianjie Guo, Hu Shi, Qichun Song, Zhaoying Liu","doi":"10.1109/ICARM52023.2021.9536078","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536078","url":null,"abstract":"Robot-assisted technology for minimally invasive surgery (MIS) can improve the quality of surgery and help surgeons carry out surgery more easily. The remote center of motion (RCM) mechanism with multiple degrees of freedom (DoFs) is one of the key parts of the MIS robot. A linear motion unit is usually used to realize the translation of the surgical tool along its axis in existing RCM mechanisms, which occupies a large space above the patient’s body and is prone to interference. Based on the double parallelogram mechanism, an RCM mechanism is proposed, which can realize pitch and translation motion of the surgical tool. The geometrical modeling is introduced first to prove that there is a remote center of the mechanism during its movement. Then, the inverse kinematics is analyzed on the basis of geometrical modeling of the mechanism. Furthermore, the singularity, Jacobian matrix and the kinematic performance of the mechanism are analyzed, and the workspace is verified with the kinematics equation. Finally, a prototype based on the proposed RCM mechanism was built to test its function. The results indicate that the remote center motion can be realized by this mechanism, and it can be used to develop an MIS manipulator.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536198
P. Huang, Wang Yuan, Qinjian Li, Ying Feng
In this paper, an optimal controller is designed and applied to the lower-limb exoskeleton robot, which could improve the robustness under nonlinear perturbations. In order to derive the optimal controller, we build the modeling of the exoskeleton robot to simplify the structure of the robot, and then we define a cost function, because the cost function is difficult to solve, so we adopt the function approximation method to approximate its optimal value, and the optimal control is obtained by solving the Hamiltonian equation. Finally, simulation studies are carried out. These simulation studies verify that the controller has a good performance even in the presence of disturbance.
{"title":"Neural Network-Based Optimal Control of a Lower-limb Exoskeleton Robot","authors":"P. Huang, Wang Yuan, Qinjian Li, Ying Feng","doi":"10.1109/ICARM52023.2021.9536198","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536198","url":null,"abstract":"In this paper, an optimal controller is designed and applied to the lower-limb exoskeleton robot, which could improve the robustness under nonlinear perturbations. In order to derive the optimal controller, we build the modeling of the exoskeleton robot to simplify the structure of the robot, and then we define a cost function, because the cost function is difficult to solve, so we adopt the function approximation method to approximate its optimal value, and the optimal control is obtained by solving the Hamiltonian equation. Finally, simulation studies are carried out. These simulation studies verify that the controller has a good performance even in the presence of disturbance.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132938177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536213
Yi Gong, Zongping Yang, Sichen Wang, Jintao Zhu, Tianshuo Huang, Jun Zhang
The folding function of foldable flapping-wing robots (FFWRs) plays an important role in practical application. In this work, we designed a foldable wing mechanism for studying its energy efficiency improvement potential. The foldable wing mechanism allows the entire wing membrane to fold and expand through the movement of components. We mainly studied the feasible foldable airfoil skeleton, and carried out kinematics and aerodynamic simulations on it, and compared the simulation results with the non-folding airfoil. The results show that when the flapping frequency is the same as 2Hz and the robot forward speed is 5m/s to 10m/s, the average lift force and thrust of the foldable airfoil are smaller than the ones of the non-folding airfoil. The energy loss will be reduced during takeoff of the robot with the foldable wings. The results in this paper can provide a reference for the subsequent wing improvement and flapping-wing robots design.
{"title":"Foldable Wings Improve Energy Efficiency of Bio-Inspired Flapping-Wing Robot during Takeoff","authors":"Yi Gong, Zongping Yang, Sichen Wang, Jintao Zhu, Tianshuo Huang, Jun Zhang","doi":"10.1109/ICARM52023.2021.9536213","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536213","url":null,"abstract":"The folding function of foldable flapping-wing robots (FFWRs) plays an important role in practical application. In this work, we designed a foldable wing mechanism for studying its energy efficiency improvement potential. The foldable wing mechanism allows the entire wing membrane to fold and expand through the movement of components. We mainly studied the feasible foldable airfoil skeleton, and carried out kinematics and aerodynamic simulations on it, and compared the simulation results with the non-folding airfoil. The results show that when the flapping frequency is the same as 2Hz and the robot forward speed is 5m/s to 10m/s, the average lift force and thrust of the foldable airfoil are smaller than the ones of the non-folding airfoil. The energy loss will be reduced during takeoff of the robot with the foldable wings. The results in this paper can provide a reference for the subsequent wing improvement and flapping-wing robots design.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133414824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536059
Yangyi Liu, Zihao Yuan, Yangping Li, Haifeng Zhao
The subsurface exploration with autonomous burrowing robot might be a low-cost and high-efficient solution for a future extraterrestrial mission on the Moon. To enable a locomotive mechanism drilling into an uncertain lunar formation composed of soils and rocks, the design of trajectory planning scheme is a very challenging task. In this work, a trajectory planning method in a three-dimensional (3-D) geological domain with distributed obstacles is proposed. An improved pruning version of Rapid-exploration Random Tree algorithm was first developed, then a set of candidate paths was generated. By introducing the evaluation functions, the optimal path was selected among a group of recommended paths. At last, Bezier parametric curve was utilized to enhance the smoothness of robotic trajectory. The method was examined and discussed through numerical experiments. The simulation results show that this method may adapt to a variety of underground environments and different task requirements. Overall, the proposed method provides a powerful multi-objective optimization strategy to operate an autonomous burrowing robot in lunar subsurface. It can be further generalized to consider more factors in an intelligent decision-making manner.
{"title":"A Three-Dimensional Path Planning Method of Autonomous Burrowing Robot for Lunar Subsurface Exploration","authors":"Yangyi Liu, Zihao Yuan, Yangping Li, Haifeng Zhao","doi":"10.1109/ICARM52023.2021.9536059","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536059","url":null,"abstract":"The subsurface exploration with autonomous burrowing robot might be a low-cost and high-efficient solution for a future extraterrestrial mission on the Moon. To enable a locomotive mechanism drilling into an uncertain lunar formation composed of soils and rocks, the design of trajectory planning scheme is a very challenging task. In this work, a trajectory planning method in a three-dimensional (3-D) geological domain with distributed obstacles is proposed. An improved pruning version of Rapid-exploration Random Tree algorithm was first developed, then a set of candidate paths was generated. By introducing the evaluation functions, the optimal path was selected among a group of recommended paths. At last, Bezier parametric curve was utilized to enhance the smoothness of robotic trajectory. The method was examined and discussed through numerical experiments. The simulation results show that this method may adapt to a variety of underground environments and different task requirements. Overall, the proposed method provides a powerful multi-objective optimization strategy to operate an autonomous burrowing robot in lunar subsurface. It can be further generalized to consider more factors in an intelligent decision-making manner.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131846935","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}
Point cloud registration is a classical problem in advanced robot perception. Despite having been widely studied, the registration of large-scale point clouds still remains challenging in terms of both efficiency and accuracy. In this paper, aiming at the registration in large-scale structural scenes that contains numerous line-features, we propose a line-based efficient and robust registration algorithm for robot perception. Concretely, we first extract lines from point clouds and use the line-features to perform the registration, which decreases the scale of algorithm’s input and decouples the rotation and the translation sub-problems. Consequently, it reduces the complexity of registration problem. We then solve the rotation and translation sub-problems using the branch-and-bound algorithm, which ensures the accuracy and robustness of registration. In translation sub-problem, we propose two strategies to adapt to the registration problem in different scenes, the one is universal algorithm, the other is decoupled algorithm. Extensive experiments are performed on both synthetic and real-world data to demonstrate the advantages of our method.
{"title":"Efficient and Robust Line-based Registration Algorithm for Robot Perception Under Large-scale Structural Scenes","authors":"Guang Chen, Yinlong Liu, Jinhu Dong, Lijun Zhang, Haotian Liu, Bo Zhang, Alois Knoll","doi":"10.1109/ICARM52023.2021.9536185","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536185","url":null,"abstract":"Point cloud registration is a classical problem in advanced robot perception. Despite having been widely studied, the registration of large-scale point clouds still remains challenging in terms of both efficiency and accuracy. In this paper, aiming at the registration in large-scale structural scenes that contains numerous line-features, we propose a line-based efficient and robust registration algorithm for robot perception. Concretely, we first extract lines from point clouds and use the line-features to perform the registration, which decreases the scale of algorithm’s input and decouples the rotation and the translation sub-problems. Consequently, it reduces the complexity of registration problem. We then solve the rotation and translation sub-problems using the branch-and-bound algorithm, which ensures the accuracy and robustness of registration. In translation sub-problem, we propose two strategies to adapt to the registration problem in different scenes, the one is universal algorithm, the other is decoupled algorithm. Extensive experiments are performed on both synthetic and real-world data to demonstrate the advantages of our method.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131852639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536180
Xiangyang Zhou, Weiqian Wang, Yanjun Shi
Aiming at the serious influence of multi-source disturbances on the control precision of inertially stabilized platform (ISP), an accurate identification modeling method based on RBFNN for the ISP system is proposed. Since the ISP control system under the multi-source disturbances is a nonlinear, parameters uncertain, and time-varying system, the conventional modeling method cannot accurately describe the system characteristics. Therefore, more accurate modeling should be conducted. In the proposed modeling method, an off-line/on-line composite identification method is proposed to ensure the real-time performance in the dynamic adjustment process of the model, and the basis for the design of adaptive controller is designed. Besides, the simulation analysis and the experimental validation are performed and consistent conclusions are gotten.
{"title":"Identification Modeling Based on RBFNN for an Aerial Inertially Stabilized Platform*","authors":"Xiangyang Zhou, Weiqian Wang, Yanjun Shi","doi":"10.1109/ICARM52023.2021.9536180","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536180","url":null,"abstract":"Aiming at the serious influence of multi-source disturbances on the control precision of inertially stabilized platform (ISP), an accurate identification modeling method based on RBFNN for the ISP system is proposed. Since the ISP control system under the multi-source disturbances is a nonlinear, parameters uncertain, and time-varying system, the conventional modeling method cannot accurately describe the system characteristics. Therefore, more accurate modeling should be conducted. In the proposed modeling method, an off-line/on-line composite identification method is proposed to ensure the real-time performance in the dynamic adjustment process of the model, and the basis for the design of adaptive controller is designed. Besides, the simulation analysis and the experimental validation are performed and consistent conclusions are gotten.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115214224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536108
Lixu Deng, Zhiwen Li, Yongping Pan
Robot interaction control with fixed impedance parameters usually fails to achieve the desired interaction behavior, motivating the introduction of variable impedance or admittance control. A gradient-descent (GD) impedance learning approach with a limited iteration number can make robots more compliant by minimizing an objective function. However, due to the nature of GD optimization, impedance parameters can not be adjusted in time by this approach, resulting in degraded robot compliance. This paper combines GD optimization with sparse online Gaussian process (SOGP) to develop a GD-based SOGP (GD-SOGP) impedance learning approach for variable admittance control. A high-fidelity mathematical model of a 7-DoF collaborative robot called Panda is applied for simulation studies. It is shown that the proposed GD-SOGP impedance learning can make the robot more compliant and outperforms the GD impedance learning in terms of impedance convergence.
{"title":"Sparse Online Gaussian Process Impedance Learning for Multi-DoF Robotic Arms","authors":"Lixu Deng, Zhiwen Li, Yongping Pan","doi":"10.1109/ICARM52023.2021.9536108","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536108","url":null,"abstract":"Robot interaction control with fixed impedance parameters usually fails to achieve the desired interaction behavior, motivating the introduction of variable impedance or admittance control. A gradient-descent (GD) impedance learning approach with a limited iteration number can make robots more compliant by minimizing an objective function. However, due to the nature of GD optimization, impedance parameters can not be adjusted in time by this approach, resulting in degraded robot compliance. This paper combines GD optimization with sparse online Gaussian process (SOGP) to develop a GD-based SOGP (GD-SOGP) impedance learning approach for variable admittance control. A high-fidelity mathematical model of a 7-DoF collaborative robot called Panda is applied for simulation studies. It is shown that the proposed GD-SOGP impedance learning can make the robot more compliant and outperforms the GD impedance learning in terms of impedance convergence.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117180758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536155
Jianxiao Chen, Guang Chen, Zhijun Li, Ya Wu, Alois Knoll
Predicting the future trajectory of different traffic agents in the complex traffic environments plays an important role in keeping the driving safety of self-driving cars, especially on urban roads. In the most of the existing works, researchers always use the long short-term memory network (LSTM) to solve this problem, since the LSTM has powerful capability for capturing the temporal dependency in motion trajectory. However, they only consider forward time cues and ignore the spatial-temporal correlations between traffic agents. Inspired by the previous work which utilizing the spatial-temporal graph, we design a spatial attention based spatial-temporal graph convolutional network, which assigns different attention weight to the the graph to take the different social interactions among the self-driving cars into consideration. We conduct extensive experiments on the benchmark InD to compare our method against many baselines. The experiment results indicate the superiority of our method than previous method, about 22% and 17% improvement on the metric of ADE and FDE respectively.
{"title":"Attention Based Graph Convolutional Networks for Trajectory Prediction","authors":"Jianxiao Chen, Guang Chen, Zhijun Li, Ya Wu, Alois Knoll","doi":"10.1109/ICARM52023.2021.9536155","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536155","url":null,"abstract":"Predicting the future trajectory of different traffic agents in the complex traffic environments plays an important role in keeping the driving safety of self-driving cars, especially on urban roads. In the most of the existing works, researchers always use the long short-term memory network (LSTM) to solve this problem, since the LSTM has powerful capability for capturing the temporal dependency in motion trajectory. However, they only consider forward time cues and ignore the spatial-temporal correlations between traffic agents. Inspired by the previous work which utilizing the spatial-temporal graph, we design a spatial attention based spatial-temporal graph convolutional network, which assigns different attention weight to the the graph to take the different social interactions among the self-driving cars into consideration. We conduct extensive experiments on the benchmark InD to compare our method against many baselines. The experiment results indicate the superiority of our method than previous method, about 22% and 17% improvement on the metric of ADE and FDE respectively.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116137206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1109/ICARM52023.2021.9536161
Zhihao Zhang, Fei Meng, Lei Wang, Ru Kang, Sai Gu, Botao Liu, Xuxiao Fan, A. Ming, Qiang Huang
Wheel-legged robots have the potential of highly dynamic locomotion. The development of Wheel-legged robots might extend the capabilities and provide a solution to the challenges of legged robots. We first modeled our self-developed quadruped experimental platform and expanded our previous work. For the scene of long-range and high-speed movement, we propose a deviation-based online locomotion planner to improve the efficiency and stability of a wheeled quadrupedal robot by reducing unnecessary steps. In the process, relative deviation values are obtained by comparing the ideal foothold reference with the actual wheel position and used to generate locomotion commands. With a control framework of robot locomotion based on a whole-body controller, the robot can move stably for a long distance in the simulation environment. The simulation results also show that compared with the time-based scheduler, this approach has advantages in efficiency and stability.
{"title":"Online Locomotion Planner For Wheeled Quadrupedal Robot Using Deviation Based Scheduler","authors":"Zhihao Zhang, Fei Meng, Lei Wang, Ru Kang, Sai Gu, Botao Liu, Xuxiao Fan, A. Ming, Qiang Huang","doi":"10.1109/ICARM52023.2021.9536161","DOIUrl":"https://doi.org/10.1109/ICARM52023.2021.9536161","url":null,"abstract":"Wheel-legged robots have the potential of highly dynamic locomotion. The development of Wheel-legged robots might extend the capabilities and provide a solution to the challenges of legged robots. We first modeled our self-developed quadruped experimental platform and expanded our previous work. For the scene of long-range and high-speed movement, we propose a deviation-based online locomotion planner to improve the efficiency and stability of a wheeled quadrupedal robot by reducing unnecessary steps. In the process, relative deviation values are obtained by comparing the ideal foothold reference with the actual wheel position and used to generate locomotion commands. With a control framework of robot locomotion based on a whole-body controller, the robot can move stably for a long distance in the simulation environment. The simulation results also show that compared with the time-based scheduler, this approach has advantages in efficiency and stability.","PeriodicalId":367307,"journal":{"name":"2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123459318","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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