Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551466
Omar Al-Buraiki, P. Payeur
This paper examines task allocation in multi-robot systems in the context where a suitability level of the specialized robots is considered. Based on the assumption that each individual agent possesses specialized functional capabilities and that the expected tasks impose specific requirements, a formulation of the agents' specialization is defined to estimate individual agents' task allocation probabilities. The original task allocation process involves a centralized matching scheme to associate each agent's suitability level with corresponding detected tasks. Then, the task-agent matching scheme is expanded to coordinate the most specialized agent or group of agents while also considering availability factors. Early experimental results are presented and analyzed to demonstrate the effectiveness of the proposed framework.
{"title":"Task Allocation in Multi-Robot Systems Based on the Suitability Level of the Individual Agents","authors":"Omar Al-Buraiki, P. Payeur","doi":"10.1109/CASE49439.2021.9551466","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551466","url":null,"abstract":"This paper examines task allocation in multi-robot systems in the context where a suitability level of the specialized robots is considered. Based on the assumption that each individual agent possesses specialized functional capabilities and that the expected tasks impose specific requirements, a formulation of the agents' specialization is defined to estimate individual agents' task allocation probabilities. The original task allocation process involves a centralized matching scheme to associate each agent's suitability level with corresponding detected tasks. Then, the task-agent matching scheme is expanded to coordinate the most specialized agent or group of agents while also considering availability factors. Early experimental results are presented and analyzed to demonstrate the effectiveness of the proposed framework.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439772","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551498
Miao Yu, Wu Zhao, Kai Zhang, Xin Guo
Stimulus-responsive polymer sensors are important components of micro/nano-mechanical systems (M/NEMS), which are widely used in many frontier fields. As an important part of smart materials, the volume, mass, or elasticity of pH-sensitive polymers can shift with pH values, which can be used in many fields such as biology, chemistry and micro/nano electromechanical system. However, few studies on the micromechanical properties of smart materials have been reported until now. In this paper, a comparative study of the single-molecule mechanical elasticity of pH-sensitive polymeric polyacrylic acid (PAA) at pH change was performed using atomic force microscopy-based single-molecule force spectroscopy (SMFS). The results show that the single-chain conformation of PAA undergoes from collapse to full extension with increasing pH and the energy difference between different conformations is obtained, which leads to a novel design concept of a molecular motor (switch). It is expected that our study can provide a theoretical basis and data support for the design of new polymers and smart sensors with multiple responses.
{"title":"Micromechanical properties of pH-sensitive smart materials","authors":"Miao Yu, Wu Zhao, Kai Zhang, Xin Guo","doi":"10.1109/CASE49439.2021.9551498","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551498","url":null,"abstract":"Stimulus-responsive polymer sensors are important components of micro/nano-mechanical systems (M/NEMS), which are widely used in many frontier fields. As an important part of smart materials, the volume, mass, or elasticity of pH-sensitive polymers can shift with pH values, which can be used in many fields such as biology, chemistry and micro/nano electromechanical system. However, few studies on the micromechanical properties of smart materials have been reported until now. In this paper, a comparative study of the single-molecule mechanical elasticity of pH-sensitive polymeric polyacrylic acid (PAA) at pH change was performed using atomic force microscopy-based single-molecule force spectroscopy (SMFS). The results show that the single-chain conformation of PAA undergoes from collapse to full extension with increasing pH and the energy difference between different conformations is obtained, which leads to a novel design concept of a molecular motor (switch). It is expected that our study can provide a theoretical basis and data support for the design of new polymers and smart sensors with multiple responses.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124434342","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551648
Robin Baran, Xiao Tan, P. Várnai, Pian Yu, Sofie Ahlberg, Meng Guo, Wenceslao Shaw-Cortez, Dimos V. Dimarogonas
In this paper, we propose a ROS software package for planning and control of robotic systems with a human-in-the-Ioop focus. The software uses temporal logic specifications, specifically Linear Temporal Logic, for a language-based method to develop correct-by-design high level robot plans. The approach is structured to allow a human to adjust the high-level plan online. A human may also take control of the robot (in a low-level control fashion), but the software prevents the human from implementing dangerous behaviour that would violate the high-level task specification. Finally, the planner is able to learn human-preferred high-level tasks by tracking human low-level control inputs in an inverse learning framework. The proposed approach is demonstrated in a warehouse setting with multiple robot agents to showcase the efficacy of the proposed solution.
{"title":"A ROS Package for Human-In-the-Loop Planning and Control under Linear Temporal Logic Tasks","authors":"Robin Baran, Xiao Tan, P. Várnai, Pian Yu, Sofie Ahlberg, Meng Guo, Wenceslao Shaw-Cortez, Dimos V. Dimarogonas","doi":"10.1109/CASE49439.2021.9551648","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551648","url":null,"abstract":"In this paper, we propose a ROS software package for planning and control of robotic systems with a human-in-the-Ioop focus. The software uses temporal logic specifications, specifically Linear Temporal Logic, for a language-based method to develop correct-by-design high level robot plans. The approach is structured to allow a human to adjust the high-level plan online. A human may also take control of the robot (in a low-level control fashion), but the software prevents the human from implementing dangerous behaviour that would violate the high-level task specification. Finally, the planner is able to learn human-preferred high-level tasks by tracking human low-level control inputs in an inverse learning framework. The proposed approach is demonstrated in a warehouse setting with multiple robot agents to showcase the efficacy of the proposed solution.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116668985","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 cascading failure is a typical failure propagation process which can cause significant consequence to the power system. It can be triggered by the vulnerable set composed of combinations of transmission lines with specific failures. So it is of great significance to identify the vulnerable set. In this paper, we propose an identification model for the vulnerable set under deep learning framework. The main part of the model consists of autoencoder and classification network for reducing dimensionality and identifying vulnerable set respectively. The model is trained by the data generated from cascading failure simulation platform. We conduct experiments on IEEE 30-Bus and 200-Bus systems with different initial failures to validate the identification and generalization capability. And the time consumption is also discussed to demonstrate the efficiency of the model. All of the indicators prove that the model is capable of identifying the vulnerable set effectively.
{"title":"Identifying Vulnerable Set of Cascading Failure in Power Grid Using Deep Learning Framework","authors":"Sizhe He, Yadong Zhou, Jiang Wu, Zhanbo Xu, X. Guan, Wei Chen, Ting Liu","doi":"10.1109/CASE49439.2021.9551411","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551411","url":null,"abstract":"The cascading failure is a typical failure propagation process which can cause significant consequence to the power system. It can be triggered by the vulnerable set composed of combinations of transmission lines with specific failures. So it is of great significance to identify the vulnerable set. In this paper, we propose an identification model for the vulnerable set under deep learning framework. The main part of the model consists of autoencoder and classification network for reducing dimensionality and identifying vulnerable set respectively. The model is trained by the data generated from cascading failure simulation platform. We conduct experiments on IEEE 30-Bus and 200-Bus systems with different initial failures to validate the identification and generalization capability. And the time consumption is also discussed to demonstrate the efficiency of the model. All of the indicators prove that the model is capable of identifying the vulnerable set effectively.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121140597","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551685
Sean McGovern, Jing Xiao
Many industrial robotic applications require a manipulator to move the end-effector in a constrained motion to cover a surface region, including painting, spray coating, abrasive blasting, polishing, shotcreting. etc. The manipulator has to satisfy both task constraints imposed on the end-effector (such as maintaining certain distance and angle with respect to the target surface while traversing it) and manipulator joint constraints. Given a robot manipulator and a target surface patch, an important question is whether there exists a feasible path for the manipulator to move continuously along the surface patch to cover it entirely while satisfying both manipulator and task constraints. This question is largely open as it has not been addressed systematically, even though there is substantial literature on path planning of constrained manipulation motion. In this paper, we introduce a general and efficient method to provide answers to this question.
{"title":"Efficient Feasibility Checking on Continuous Coverage Motion for Constrained Manipulation","authors":"Sean McGovern, Jing Xiao","doi":"10.1109/CASE49439.2021.9551685","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551685","url":null,"abstract":"Many industrial robotic applications require a manipulator to move the end-effector in a constrained motion to cover a surface region, including painting, spray coating, abrasive blasting, polishing, shotcreting. etc. The manipulator has to satisfy both task constraints imposed on the end-effector (such as maintaining certain distance and angle with respect to the target surface while traversing it) and manipulator joint constraints. Given a robot manipulator and a target surface patch, an important question is whether there exists a feasible path for the manipulator to move continuously along the surface patch to cover it entirely while satisfying both manipulator and task constraints. This question is largely open as it has not been addressed systematically, even though there is substantial literature on path planning of constrained manipulation motion. In this paper, we introduce a general and efficient method to provide answers to this question.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127099779","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551533
Alexander Schmidt, Christian Kotschote, O. Riedel
Workpiece tolerances in manufacturing welding applications can lead to a deviation of the welding tool from the workpiece. Such a tool offset leads to reduced welding quality. This problem can be solved by measuring the exact workpiece geometry and orientation in advance of the welding process. However, measuring the workpiece geometry for each workpiece increases the manufacturing time. Therefore, this work presents a novel approach for an in-process tool offset observer. The observer model is retrieved via supervised learning methods based on real experimental welding data. The methods for extracting features from time-series data are described. A benchmark for multiple supervised learning methods and sensor types is presented. The accuracy of the trained models is tested by welding experiments. The significance of this paper is the demonstration of the feasibility of in-process tool offset estimation for robotic arc welding applications.
{"title":"Supervised learning based observer for in-process tool offset estimation in robotic arc welding applications","authors":"Alexander Schmidt, Christian Kotschote, O. Riedel","doi":"10.1109/CASE49439.2021.9551533","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551533","url":null,"abstract":"Workpiece tolerances in manufacturing welding applications can lead to a deviation of the welding tool from the workpiece. Such a tool offset leads to reduced welding quality. This problem can be solved by measuring the exact workpiece geometry and orientation in advance of the welding process. However, measuring the workpiece geometry for each workpiece increases the manufacturing time. Therefore, this work presents a novel approach for an in-process tool offset observer. The observer model is retrieved via supervised learning methods based on real experimental welding data. The methods for extracting features from time-series data are described. A benchmark for multiple supervised learning methods and sensor types is presented. The accuracy of the trained models is tested by welding experiments. The significance of this paper is the demonstration of the feasibility of in-process tool offset estimation for robotic arc welding applications.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127448874","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551617
Deniz Ugur, O. Bebek
This paper presents a fast, energy-efficient, and low computational cost traversal solution on sloped terrain. The use of grid-based search algorithms requires high computational power and takes a long time because almost every point on the map is visited. An approach that does not depend on the global map but can also navigate towards the target can be presented as a new solution. A cost map for motion planning using depth field and color image data is formed in real-time. The proposed motion planning algorithm, named SAFARI, utilizes four cost layers to efficiently evaluate its surroundings. To reduce the computational overhead, only select features are evaluated and the rover's motion planning cycle speed is increased. SAFARI has been tested against path planning alternatives and has also been proven to work with simulations and field tests. This concept is expected to be used in space applications and cave exploration tasks.
{"title":"Fast and Efficient Terrain-Aware Motion Planning for Exploration Rovers","authors":"Deniz Ugur, O. Bebek","doi":"10.1109/CASE49439.2021.9551617","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551617","url":null,"abstract":"This paper presents a fast, energy-efficient, and low computational cost traversal solution on sloped terrain. The use of grid-based search algorithms requires high computational power and takes a long time because almost every point on the map is visited. An approach that does not depend on the global map but can also navigate towards the target can be presented as a new solution. A cost map for motion planning using depth field and color image data is formed in real-time. The proposed motion planning algorithm, named SAFARI, utilizes four cost layers to efficiently evaluate its surroundings. To reduce the computational overhead, only select features are evaluated and the rover's motion planning cycle speed is increased. SAFARI has been tested against path planning alternatives and has also been proven to work with simulations and field tests. This concept is expected to be used in space applications and cave exploration tasks.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123271564","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551435
Ashfaq Farooqui, Fredrik Hagebring, Martin Fabian
A tool, MIDES, for automatic learning of models and supervisors for discrete event systems is presented. The tool interfaces with a simulation of the target system to learn a behavioral model through interaction. There are several different algorithms to choose from depending on the intended outcome. Moreover, given a set of specifications, the tool learns a supervisor that can help ensure the controlled system guarantees the specifications. Furthermore, the state-space explosion problem is addressed by learning a modular supervisor. In this paper, we introduce the tool, its interfaces, and algorithms. We demonstrate the usefulness through several case studies.
{"title":"MIDES: A Tool for Supervisor Synthesis via Active Learning","authors":"Ashfaq Farooqui, Fredrik Hagebring, Martin Fabian","doi":"10.1109/CASE49439.2021.9551435","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551435","url":null,"abstract":"A tool, MIDES, for automatic learning of models and supervisors for discrete event systems is presented. The tool interfaces with a simulation of the target system to learn a behavioral model through interaction. There are several different algorithms to choose from depending on the intended outcome. Moreover, given a set of specifications, the tool learns a supervisor that can help ensure the controlled system guarantees the specifications. Furthermore, the state-space explosion problem is addressed by learning a modular supervisor. In this paper, we introduce the tool, its interfaces, and algorithms. We demonstrate the usefulness through several case studies.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"75 29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123406365","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551415
Negin Amirshirzad, Begum Sunal, O. Bebek, Erhan Öztop
This paper focuses on a learning from demonstration approach for autonomous medical suturing. A conditional neural network is used to learn and generate suturing primitives trajectories which were conditioned on desired context points. Using our designed GUI a user could plan and select suturing insertion points. Given the insertion point our model generates joint trajectories on real time satisfying this condition. The generated trajectories combined with a kinematic feedback loop were used to drive an 11-DOF robotic system and shows satisfying abilities to learn and perform suturing primitives autonomously having only a few demonstrations of the movements.
{"title":"Learning Medical Suturing Primitives for Autonomous Suturing","authors":"Negin Amirshirzad, Begum Sunal, O. Bebek, Erhan Öztop","doi":"10.1109/CASE49439.2021.9551415","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551415","url":null,"abstract":"This paper focuses on a learning from demonstration approach for autonomous medical suturing. A conditional neural network is used to learn and generate suturing primitives trajectories which were conditioned on desired context points. Using our designed GUI a user could plan and select suturing insertion points. Given the insertion point our model generates joint trajectories on real time satisfying this condition. The generated trajectories combined with a kinematic feedback loop were used to drive an 11-DOF robotic system and shows satisfying abilities to learn and perform suturing primitives autonomously having only a few demonstrations of the movements.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123757896","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}
Water visibility is a critical matter for underwater robots during operations, both for getting clear views of the environment, and as a calm and disturbance-free operating region for the manipulators to perform sampling or other operations. In reality, calm and clear water is not only restricted by the natural conditions, but also often hindered by the propeller operations from the robots themselves. Frequent gesture adjustments during manipulator operations are particularly stir-inducing from state-of-the-art underwater manipulative robots. In this work, tackling the flow disturbance issue, a novel underwater robotic platform was proposed with a jellyfish-inspired holonomic platform driven by propellers, a flow-deflection middle layer as an adjustable isolation, and a soft-robotic manipulator mounted below the bottom for operations. Compared with state-of-the-art works, the proposed platform achieved holonomic underwater locomotion with the vertical main direction having significantly reduced flow resistance; the flow-deflection layer could create a flow-calm region of 18.5 times larger underneath for the manipulator operations. A prototype robot was fabricated, and tested in closed- and open-water conditions. Results were compared to flow-simulation results with good agreements, verifying that the proposed jellyfish-inspired robotic concept was effective in both asymmetric underwater locomotion and reducing water disturbances for underwater manipulator operations.
{"title":"An Omnidirectional Robotic Platform with a Vertically Mounted Manipulator for Seabed Operation","authors":"Binbin Zhang, Kailuan Tang, Yishan Chen, Kehan Zou, Yin Xiao, Zhonggui Fang, Qinlin Tan, Zhongzhe Shen, Sicong Liu, Juan Yi, Zheng Wang","doi":"10.1109/CASE49439.2021.9551420","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551420","url":null,"abstract":"Water visibility is a critical matter for underwater robots during operations, both for getting clear views of the environment, and as a calm and disturbance-free operating region for the manipulators to perform sampling or other operations. In reality, calm and clear water is not only restricted by the natural conditions, but also often hindered by the propeller operations from the robots themselves. Frequent gesture adjustments during manipulator operations are particularly stir-inducing from state-of-the-art underwater manipulative robots. In this work, tackling the flow disturbance issue, a novel underwater robotic platform was proposed with a jellyfish-inspired holonomic platform driven by propellers, a flow-deflection middle layer as an adjustable isolation, and a soft-robotic manipulator mounted below the bottom for operations. Compared with state-of-the-art works, the proposed platform achieved holonomic underwater locomotion with the vertical main direction having significantly reduced flow resistance; the flow-deflection layer could create a flow-calm region of 18.5 times larger underneath for the manipulator operations. A prototype robot was fabricated, and tested in closed- and open-water conditions. Results were compared to flow-simulation results with good agreements, verifying that the proposed jellyfish-inspired robotic concept was effective in both asymmetric underwater locomotion and reducing water disturbances for underwater manipulator operations.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115563415","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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