Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125755
P. Pradhan, Arijit Sen, Mangal Kothari, K. Rajawat
Distributed optimisation (DO) problems in application to networked multi-agent system (MAS) have been an intriguing topic for research among different research communities. Despite the substantial number of works in this field over the past decade, the existing literature lacks a generalised algorithm for solving the DO problem for a strongly-connected weight unbalanced graph. This paper presents an information state dynamics for optimising the convex global objective function in a distributed manner under a strongly-connected weight-unbalanced digraph. Unlike few of the existing algorithms, the proposed dynamics does not require any global information, rather it solely depends on the locally available information and the information that the agent receives from the neighbours only. Numerical simulations with a comparative study with the state-of-the-art algorithm solving a DO problem under a weight-unbalanced digraph are also demonstrated in the paper to prove the claims.
{"title":"Distributed Optimisation under a Weight-unbalanced Digraph","authors":"P. Pradhan, Arijit Sen, Mangal Kothari, K. Rajawat","doi":"10.1109/ICARA56516.2023.10125755","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125755","url":null,"abstract":"Distributed optimisation (DO) problems in application to networked multi-agent system (MAS) have been an intriguing topic for research among different research communities. Despite the substantial number of works in this field over the past decade, the existing literature lacks a generalised algorithm for solving the DO problem for a strongly-connected weight unbalanced graph. This paper presents an information state dynamics for optimising the convex global objective function in a distributed manner under a strongly-connected weight-unbalanced digraph. Unlike few of the existing algorithms, the proposed dynamics does not require any global information, rather it solely depends on the locally available information and the information that the agent receives from the neighbours only. Numerical simulations with a comparative study with the state-of-the-art algorithm solving a DO problem under a weight-unbalanced digraph are also demonstrated in the paper to prove the claims.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122302719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125971
Andreas Mitakidis, Sotirios N. Aspragkathos, Fotis Panetsos, G. Karras, K. Kyriakopoulos
In this work, a deep Reinforcement Learning control scheme is developed in order to execute autonomous tracking of an unmanned ground vehicle (UGV) with a multirotor unmanned aerial vehicle (UAV). The UAV is equipped with a downward looking camera and the detection of the target UGV is achieved through a convolutional neural network (CNN). The deep RL control policy is deployed as a cascade position controller, which commands the inner attitude controller of the autopilot, and achieves the following of the UGV despite the aggressive maneuvers of the target. The efficacy of the proposed framework is demonstrated via a set of outdoor experiments using an octocopter flying above the ground vehicle.
{"title":"A Deep Reinforcement Learning Visual Servoing Control Strategy for Target Tracking Using a Multirotor UAV","authors":"Andreas Mitakidis, Sotirios N. Aspragkathos, Fotis Panetsos, G. Karras, K. Kyriakopoulos","doi":"10.1109/ICARA56516.2023.10125971","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125971","url":null,"abstract":"In this work, a deep Reinforcement Learning control scheme is developed in order to execute autonomous tracking of an unmanned ground vehicle (UGV) with a multirotor unmanned aerial vehicle (UAV). The UAV is equipped with a downward looking camera and the detection of the target UGV is achieved through a convolutional neural network (CNN). The deep RL control policy is deployed as a cascade position controller, which commands the inner attitude controller of the autopilot, and achieves the following of the UGV despite the aggressive maneuvers of the target. The efficacy of the proposed framework is demonstrated via a set of outdoor experiments using an octocopter flying above the ground vehicle.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122070563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10126050
Alexandra Bernadotte
This paper highlights the progress toward securing teleoperating devices over the past ten years of active technology development. The relevance of this issue lies in the widespread development of teleoperating systems with a small number of systems allowed for operations. Anomalous behavior of the operating device, caused by a disruption in the normal functioning of the system modules, can be associated with remote attacks and exploitation of vulnerabilities, which can lead to fatal consequences. There are regulations and mandates from licensing agencies such as the US Food and Drug Administration (FDA) that place restrictions on the architecture and components of teleoperating systems. These requirements are also evolving to meet new cybersecurity threats. In particular, consumers and safety regulatory agencies are attracted by the threat of compromising hardware modules along with software insecurity. Recently, detailed security frameworks and protocols for teleoperating devices have appeared. However, a matter of intelligent autonomous controllers for analyzing anomalous and suspicious actions in the system remain unattended, as well as emergency protocols from the point of cybersecurity view. This work provides a new approach for the intraoperative cybersecurity of intelligent teleoperative surgical systems, taking into account modern requirements for implementing into the Surgical Remote Intelligent Robotic System LevshAI. The proposed principal security model allows a surgeon or autonomous agent to manage the operation process during various attacks.
{"title":"Cyber Security for Surgical Remote Intelligent Robotic Systems","authors":"Alexandra Bernadotte","doi":"10.1109/ICARA56516.2023.10126050","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10126050","url":null,"abstract":"This paper highlights the progress toward securing teleoperating devices over the past ten years of active technology development. The relevance of this issue lies in the widespread development of teleoperating systems with a small number of systems allowed for operations. Anomalous behavior of the operating device, caused by a disruption in the normal functioning of the system modules, can be associated with remote attacks and exploitation of vulnerabilities, which can lead to fatal consequences. There are regulations and mandates from licensing agencies such as the US Food and Drug Administration (FDA) that place restrictions on the architecture and components of teleoperating systems. These requirements are also evolving to meet new cybersecurity threats. In particular, consumers and safety regulatory agencies are attracted by the threat of compromising hardware modules along with software insecurity. Recently, detailed security frameworks and protocols for teleoperating devices have appeared. However, a matter of intelligent autonomous controllers for analyzing anomalous and suspicious actions in the system remain unattended, as well as emergency protocols from the point of cybersecurity view. This work provides a new approach for the intraoperative cybersecurity of intelligent teleoperative surgical systems, taking into account modern requirements for implementing into the Surgical Remote Intelligent Robotic System LevshAI. The proposed principal security model allows a surgeon or autonomous agent to manage the operation process during various attacks.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116726566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125694
Michael Troxler, Rolf Dornberger, T. Hanne
This paper discusses the moving behavior of Kilobots, particularly target search and collision avoidance. When using minimalistic robots (e.g., Kilobots), the approach to develop an algorithm is limited by computational power and sensorial functionality. Therefore, Kilobots help examine the challenges of limited simple medical nanorobots. In this paper, an algorithm is presented which is an extension of target-search and collision avoidance by introducing random walk behavior using the Lévy distribution. The results show that the random walk behavior improves the movement of Kilobots in some respects. The robots tend to discover an unknown area more efficiently in a specific time. In addition, the robots are less likely to get stuck on boarders and obstacles. On the other hand, the introduced random walk does not improve the ability of target search and collision avoidance.
{"title":"Extending the Target-Search Algorithm for Kilobots by Adding Random Walk Behavior","authors":"Michael Troxler, Rolf Dornberger, T. Hanne","doi":"10.1109/ICARA56516.2023.10125694","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125694","url":null,"abstract":"This paper discusses the moving behavior of Kilobots, particularly target search and collision avoidance. When using minimalistic robots (e.g., Kilobots), the approach to develop an algorithm is limited by computational power and sensorial functionality. Therefore, Kilobots help examine the challenges of limited simple medical nanorobots. In this paper, an algorithm is presented which is an extension of target-search and collision avoidance by introducing random walk behavior using the Lévy distribution. The results show that the random walk behavior improves the movement of Kilobots in some respects. The robots tend to discover an unknown area more efficiently in a specific time. In addition, the robots are less likely to get stuck on boarders and obstacles. On the other hand, the introduced random walk does not improve the ability of target search and collision avoidance.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124414100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125947
Alexander Coutras, Omar Obidat, Michelle Zhu, Weitian Wang
Robotics technology has been increasingly applied to healthcare contexts to enhance efficiency and safety in healthcare processes in recent years. People with mobility impairments and disabilities often require caretakers in their lives. Fortunately, robots can provide attention and assistance consistently for them instead of human caretakers. Motivated by this, we develop a robot-assisted e-health solution to empower the patients' daily lives and improve their wellbeing in this study. A transfer learning-based approach is proposed to train the robot to understand and identify patients' needs through a small dataset. Using the proposed approach, the robot is able to understand the patient's needs through speech recognition and recognize objects that the patient has requested. The proposed solution is experimentally implemented in real-world human-robot interactive healthcare contexts. Results and analysis indicate the success and accuracy of our approaches.
{"title":"JUST TELL ME: A Robot-assisted E-health Solution for People with Lower-extremity Disability","authors":"Alexander Coutras, Omar Obidat, Michelle Zhu, Weitian Wang","doi":"10.1109/ICARA56516.2023.10125947","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125947","url":null,"abstract":"Robotics technology has been increasingly applied to healthcare contexts to enhance efficiency and safety in healthcare processes in recent years. People with mobility impairments and disabilities often require caretakers in their lives. Fortunately, robots can provide attention and assistance consistently for them instead of human caretakers. Motivated by this, we develop a robot-assisted e-health solution to empower the patients' daily lives and improve their wellbeing in this study. A transfer learning-based approach is proposed to train the robot to understand and identify patients' needs through a small dataset. Using the proposed approach, the robot is able to understand the patient's needs through speech recognition and recognize objects that the patient has requested. The proposed solution is experimentally implemented in real-world human-robot interactive healthcare contexts. Results and analysis indicate the success and accuracy of our approaches.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126545316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125837
Ziyuan Ma, Huajun Gong, Xinhua Wang
With the increasing complexity and variety of mission environments, multiple-UAVs cooperative path optimization system is gradually becoming an important development direction in the future. Because the current intelligent level of UAV is difficult to meet the requirements of complex tasks, in order to improve the intelligence and collaborative ability of multiple-UAVs systems, this paper focuses on the intelligent decision-making and collaborative control of UAV in the collaborative path of multiple UAVs system. In this paper, an autonomous and innovative UAV Cooperative Path Optimization System Based on neural network of brain like attention mechanism is proposed. The experimental results show that this method has lower processing delay, can achieve positioning accuracy in a shorter time, and has higher reliability and accuracy than the traditional center controlled UAV cooperative positioning UAV method.
{"title":"Cooperative Optimal Control of UAVs Based on Brain-Attention Mechanism Neural Network","authors":"Ziyuan Ma, Huajun Gong, Xinhua Wang","doi":"10.1109/ICARA56516.2023.10125837","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125837","url":null,"abstract":"With the increasing complexity and variety of mission environments, multiple-UAVs cooperative path optimization system is gradually becoming an important development direction in the future. Because the current intelligent level of UAV is difficult to meet the requirements of complex tasks, in order to improve the intelligence and collaborative ability of multiple-UAVs systems, this paper focuses on the intelligent decision-making and collaborative control of UAV in the collaborative path of multiple UAVs system. In this paper, an autonomous and innovative UAV Cooperative Path Optimization System Based on neural network of brain like attention mechanism is proposed. The experimental results show that this method has lower processing delay, can achieve positioning accuracy in a shorter time, and has higher reliability and accuracy than the traditional center controlled UAV cooperative positioning UAV method.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132543952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125801
Hafsa Ilyas, A. Javed, Muteb Aljasem, Mustafa Alhababi
With the rapid development of sophisticated deepfakes generation methods, the realism of fake content has reached the level where it becomes difficult for human eyes to identify such high-quality fake images/videos, thus increasing the demand for developing deepfakes detection methods. The diversity in deepfakes images/videos in terms of ethnicity, illumination condition, skin tone, age, background setting, and generation algorithms makes the detection task quite difficult. To better address the aforementioned challenges, we present a novel Swish-ReLU Efficient-Net (SRE-Net) that is robust to the identification of deepfakes generated using different face-swap and face-reenactment techniques. More precisely, we fused two EfficienNet-b0 models, one with the ReLU and the other with the Swish activation function along with layer freezing to achieve better detection results. Our SRE-Net attained the average accuracy and precision of 96.5% and 97.07% on the FaceForensics++ dataset, and 88.41% and 91.28% on the DFDC-preview dataset. The high detection results demonstrate the effectiveness of SRE-Net while detecting the deepfakes generated using different manipulation algorithms.
{"title":"Fused Swish-ReLU Efficient-Net Model for Deepfakes Detection","authors":"Hafsa Ilyas, A. Javed, Muteb Aljasem, Mustafa Alhababi","doi":"10.1109/ICARA56516.2023.10125801","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125801","url":null,"abstract":"With the rapid development of sophisticated deepfakes generation methods, the realism of fake content has reached the level where it becomes difficult for human eyes to identify such high-quality fake images/videos, thus increasing the demand for developing deepfakes detection methods. The diversity in deepfakes images/videos in terms of ethnicity, illumination condition, skin tone, age, background setting, and generation algorithms makes the detection task quite difficult. To better address the aforementioned challenges, we present a novel Swish-ReLU Efficient-Net (SRE-Net) that is robust to the identification of deepfakes generated using different face-swap and face-reenactment techniques. More precisely, we fused two EfficienNet-b0 models, one with the ReLU and the other with the Swish activation function along with layer freezing to achieve better detection results. Our SRE-Net attained the average accuracy and precision of 96.5% and 97.07% on the FaceForensics++ dataset, and 88.41% and 91.28% on the DFDC-preview dataset. The high detection results demonstrate the effectiveness of SRE-Net while detecting the deepfakes generated using different manipulation algorithms.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114747703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125726
A. Elibol, N. Chong
Robots have been involved in our daily life more and more. This involvement comes along with a necessity for endowing robots to interact with real-world objects that are novel to them. Among many others, pushing is one of the important tasks for robotic arms (or manipulators) as it has been widely used in the pipeline of the more complicated tasks (e.g., grasping, singulation, reorienting, and similar other tasks.), In this paper, we present simple yet efficient path generation and push planning algorithms for pushing an object from a given point to a target point in the given grid map with static obstacles. Our path generation module aims to generate waypoints taking into account obstacles and quantizing them into circular regions in order to reduce the computational cost. The path is formed using the waypoints by minimizing the designed cost function. We also define a cost function for planning pushing steps aiming to both minimize the number of pushing actions and deviation from the path generated. We present comparative numerical results using simulated data. Our preliminary findings show promising results leaving room for further improvements.
{"title":"Toward Computationally Efficient Path Generation and Push Planning for Robotic Nonprehensile Manipulation","authors":"A. Elibol, N. Chong","doi":"10.1109/ICARA56516.2023.10125726","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125726","url":null,"abstract":"Robots have been involved in our daily life more and more. This involvement comes along with a necessity for endowing robots to interact with real-world objects that are novel to them. Among many others, pushing is one of the important tasks for robotic arms (or manipulators) as it has been widely used in the pipeline of the more complicated tasks (e.g., grasping, singulation, reorienting, and similar other tasks.), In this paper, we present simple yet efficient path generation and push planning algorithms for pushing an object from a given point to a target point in the given grid map with static obstacles. Our path generation module aims to generate waypoints taking into account obstacles and quantizing them into circular regions in order to reduce the computational cost. The path is formed using the waypoints by minimizing the designed cost function. We also define a cost function for planning pushing steps aiming to both minimize the number of pushing actions and deviation from the path generated. We present comparative numerical results using simulated data. Our preliminary findings show promising results leaving room for further improvements.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114811760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10126064
J. R. Roldan, M. Jung, Feimo Shen, D. Milutinović
In this paper, we propose a method for total knee arthroplasty (TKA) bone pose identification for robot-assisted orthopedic surgery. The TKA procedure presents a unique challenge because of a finite number of cutting trajectories, their relative locations that are not completely known, anatomical constraints and bone placement errors. Our method addresses these challenges by constructing cutting task-specific capability maps which represent the robot's ability to execute the task for various task poses. To identify the femur and tibia bone poses from the map, we develop a feasibility measure which scores the bone poses based on the volume of feasible workspace locations. Our method is successfully tested on the TCAT® surgical robot and the results reveal that it is able to properly identify anatomically feasible bone poses that have enough margin for bone placement errors during the surgery.
{"title":"Robot-Assisted Orthopedic Surgery Bone Pose Identification Using Task-Specific Capability Maps","authors":"J. R. Roldan, M. Jung, Feimo Shen, D. Milutinović","doi":"10.1109/ICARA56516.2023.10126064","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10126064","url":null,"abstract":"In this paper, we propose a method for total knee arthroplasty (TKA) bone pose identification for robot-assisted orthopedic surgery. The TKA procedure presents a unique challenge because of a finite number of cutting trajectories, their relative locations that are not completely known, anatomical constraints and bone placement errors. Our method addresses these challenges by constructing cutting task-specific capability maps which represent the robot's ability to execute the task for various task poses. To identify the femur and tibia bone poses from the map, we develop a feasibility measure which scores the bone poses based on the volume of feasible workspace locations. Our method is successfully tested on the TCAT® surgical robot and the results reveal that it is able to properly identify anatomically feasible bone poses that have enough margin for bone placement errors during the surgery.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122052032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.1109/ICARA56516.2023.10125714
Sarang Shaikh, Sule YAYILGAN YILDIRIM
In this paper, we are focusing on the use of agent-based approach to generate simulations of various scenarios for border crossing points and making technology acceptance predictions. This paper is related to the Horizon 2020 project METICOS11https://meticos-project.eu/, for which we are extracting user (traveler and border control staff) perceptions from sources such as online social networks e.g., Twitter, Web, Interviews, Questionnaires etc. However, for the scope of this paper we have only included the synthetic data for the experiments to validate the proposed simulation model. The existing studies made a strong justification for choosing this approach to model the defined problem. To the best of our knowledge, this paper is a first research study focusing on defining how agent-based modeling and simulation can be used to model border crossing scenarios and predicting the acceptance of the border control technologies by explaining travelers' profile based on synthetic data, perceptions based on manual rules. This is important for stakeholders who take decisions related to what technologies to place at the border crossing points and what features such technologies should have to improve throughputs and traveler and border staff satisfaction.
{"title":"Developing an Agent-Based Simulation Model for Predicting Technology Acceptance at Border Crossing Points","authors":"Sarang Shaikh, Sule YAYILGAN YILDIRIM","doi":"10.1109/ICARA56516.2023.10125714","DOIUrl":"https://doi.org/10.1109/ICARA56516.2023.10125714","url":null,"abstract":"In this paper, we are focusing on the use of agent-based approach to generate simulations of various scenarios for border crossing points and making technology acceptance predictions. This paper is related to the Horizon 2020 project METICOS11https://meticos-project.eu/, for which we are extracting user (traveler and border control staff) perceptions from sources such as online social networks e.g., Twitter, Web, Interviews, Questionnaires etc. However, for the scope of this paper we have only included the synthetic data for the experiments to validate the proposed simulation model. The existing studies made a strong justification for choosing this approach to model the defined problem. To the best of our knowledge, this paper is a first research study focusing on defining how agent-based modeling and simulation can be used to model border crossing scenarios and predicting the acceptance of the border control technologies by explaining travelers' profile based on synthetic data, perceptions based on manual rules. This is important for stakeholders who take decisions related to what technologies to place at the border crossing points and what features such technologies should have to improve throughputs and traveler and border staff satisfaction.","PeriodicalId":443572,"journal":{"name":"2023 9th International Conference on Automation, Robotics and Applications (ICARA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129829928","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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