Pub Date : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310858
Tanghong Wu, Fanchen Kong, Peng Peng, Zichuan Fan
Reinforcement learning based control is an effective approach to traffic light control. In terms of the Deep Q-learning Network (DQN) based traffic light control method, the reward function should be carefully designed, as it affects the performance of the control method and it also brings the challenge in standardized design. Thus, the control method would fail to perform well if the reward function was established improperly. If the reward function was too complicated, it would be time-consuming for the algorithm. To solve this problem, we proposed an intersection-model based reward function in the DQN algorithm. We investigated the different types of urban road intersection structures and analyzed their features. Then we used those features to formulate the reward function. Our model was evaluated via the simulation dataset under different road situations and got less emergency stop with 14%~32% improvement while the number of passing vehicles was also a bit more than the baseline. There were also 22% and 7% speedup in the training process under the tow training process.
{"title":"Road Intersection Model Based Reward Function Design in Deep Q-Learning Network for Traffic Light Control","authors":"Tanghong Wu, Fanchen Kong, Peng Peng, Zichuan Fan","doi":"10.1109/ICRAE50850.2020.9310858","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310858","url":null,"abstract":"Reinforcement learning based control is an effective approach to traffic light control. In terms of the Deep Q-learning Network (DQN) based traffic light control method, the reward function should be carefully designed, as it affects the performance of the control method and it also brings the challenge in standardized design. Thus, the control method would fail to perform well if the reward function was established improperly. If the reward function was too complicated, it would be time-consuming for the algorithm. To solve this problem, we proposed an intersection-model based reward function in the DQN algorithm. We investigated the different types of urban road intersection structures and analyzed their features. Then we used those features to formulate the reward function. Our model was evaluated via the simulation dataset under different road situations and got less emergency stop with 14%~32% improvement while the number of passing vehicles was also a bit more than the baseline. There were also 22% and 7% speedup in the training process under the tow training process.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123328509","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310877
Ning Wu, Shaochen Sun, Yunfeng Zou, Yang Yu
A practical question-answering (QA) system typically categorizes a new question into the frequently asked questions (FAQs) and returns the corresponding answer. Having imbalanced FAQs data is actually prevalent in general. This paper proposes a meta-learning method for imbalanced question classification. The basic idea is to generate virtual training data for zero-shot questions and then construct question prototypes for training a question classifier, thereby relieving the problem of data imbalance and improving performance of question classifier. Experiments show that the proposed method improves the overall classification performance both for English and Chinese QA tasks. Especially, the classification performance of zero annotated questions increased significantly, and the generative prototypes has minute impact on the performance of large annotated question test set.
{"title":"Imbalanced Question Classification Using Generative Prototypes","authors":"Ning Wu, Shaochen Sun, Yunfeng Zou, Yang Yu","doi":"10.1109/ICRAE50850.2020.9310877","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310877","url":null,"abstract":"A practical question-answering (QA) system typically categorizes a new question into the frequently asked questions (FAQs) and returns the corresponding answer. Having imbalanced FAQs data is actually prevalent in general. This paper proposes a meta-learning method for imbalanced question classification. The basic idea is to generate virtual training data for zero-shot questions and then construct question prototypes for training a question classifier, thereby relieving the problem of data imbalance and improving performance of question classifier. Experiments show that the proposed method improves the overall classification performance both for English and Chinese QA tasks. Especially, the classification performance of zero annotated questions increased significantly, and the generative prototypes has minute impact on the performance of large annotated question test set.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124316221","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310823
Wenqian Xie, Kaibo Shi
This paper studies the $H_{infty}$ filter design problem for a nonlinear system based on Takagi-Sugeno model. Firstly, we propose a hybrid and adaptive event-triggered scheme, which contributes to save the limited communication resource while excluding the Zeno behavior. Then, a slack Lyapunov-Krasovskii functional (LKF), the discontinuity and non-positive definiteness of which are allowed in a triggered interval, is constructed. Based on the above methods, sufficient criteria on the exponential stability of the filtering error system with a weighted $H_{infty}$ performance are established, the design method of the desired filter is achieved as well. Finally, the obtained result is verified by a tunnel diode circuit system.
{"title":"Network-based H∞ Filter Design for T-S Fuzzy Systems with a Hybrid Event-triggered Scheme","authors":"Wenqian Xie, Kaibo Shi","doi":"10.1109/ICRAE50850.2020.9310823","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310823","url":null,"abstract":"This paper studies the $H_{infty}$ filter design problem for a nonlinear system based on Takagi-Sugeno model. Firstly, we propose a hybrid and adaptive event-triggered scheme, which contributes to save the limited communication resource while excluding the Zeno behavior. Then, a slack Lyapunov-Krasovskii functional (LKF), the discontinuity and non-positive definiteness of which are allowed in a triggered interval, is constructed. Based on the above methods, sufficient criteria on the exponential stability of the filtering error system with a weighted $H_{infty}$ performance are established, the design method of the desired filter is achieved as well. Finally, the obtained result is verified by a tunnel diode circuit system.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114379192","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310899
A. Antenucci, S. Mazzaro, A. Fiorilla, L. Messina, A. Massa, W. Matta
In this paper we present an industrial implementation of an efficient method to solve the problem of the automatic precision landing for rotary-wing UAVs, ready to be used inside a cooperative fleet of drones. The realized software module and tests are part of a large industrial R&D Vitrociset project called SWARM: an AI-Enabled Command and Control (C&C) system, able to execute and review ISR missions for mini/micro cooperative fleets of heterogeneous UAVs. Preparatory to the presented results, it was the identification of a non-linear mathematical model as well as the realization of a robust PID-based control system capable of controlling a single drone of the fleet. A discrete-time Kalman filter was integrated and tested to estimate the possible displacement of the landing points, in order to improve the control law through predictive connotations in case of slow moving tags. The presented approach is featured by the balance between computational efficiency and versatility, in particular in the discovering stage of multiple and different AprilTag during the landing phase. The still under test software module uses the Open Source Robotic Operating System (ROS) libraries for both the acquisition of the data necessary to the control laws, and for the execution of the computer vision algorithms implemented for the precision landing. After analyses and simulations campaigns in a synthetic environment and multiple hardware in the loop (HIL) stress tests, the final prototype algorithm was deployed on a commercial-off-the-shelf mini-class UAV, demonstrating landing capacity on a fixed target with an error of less than ten centimeters; moreover, with slow-moving tags, appreciable tracking abilities emerged on sufficiently smooth trajectories. A special interface with the HIL flight controller was then integrated, with the capability of using its telemetry data for distributing them to all the members of the cooperative fleet, making it possible to access the real-time estimate of the states of each single drone, and making each one of them aware of the selected landing areas of the others, by navigation sensors data fusion with a five meters GPS precision.
{"title":"A ROS Based Automatic Control Implementation for Precision Landing on Slow Moving Platforms Using a Cooperative Fleet of Rotary-Wing UAVs","authors":"A. Antenucci, S. Mazzaro, A. Fiorilla, L. Messina, A. Massa, W. Matta","doi":"10.1109/ICRAE50850.2020.9310899","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310899","url":null,"abstract":"In this paper we present an industrial implementation of an efficient method to solve the problem of the automatic precision landing for rotary-wing UAVs, ready to be used inside a cooperative fleet of drones. The realized software module and tests are part of a large industrial R&D Vitrociset project called SWARM: an AI-Enabled Command and Control (C&C) system, able to execute and review ISR missions for mini/micro cooperative fleets of heterogeneous UAVs. Preparatory to the presented results, it was the identification of a non-linear mathematical model as well as the realization of a robust PID-based control system capable of controlling a single drone of the fleet. A discrete-time Kalman filter was integrated and tested to estimate the possible displacement of the landing points, in order to improve the control law through predictive connotations in case of slow moving tags. The presented approach is featured by the balance between computational efficiency and versatility, in particular in the discovering stage of multiple and different AprilTag during the landing phase. The still under test software module uses the Open Source Robotic Operating System (ROS) libraries for both the acquisition of the data necessary to the control laws, and for the execution of the computer vision algorithms implemented for the precision landing. After analyses and simulations campaigns in a synthetic environment and multiple hardware in the loop (HIL) stress tests, the final prototype algorithm was deployed on a commercial-off-the-shelf mini-class UAV, demonstrating landing capacity on a fixed target with an error of less than ten centimeters; moreover, with slow-moving tags, appreciable tracking abilities emerged on sufficiently smooth trajectories. A special interface with the HIL flight controller was then integrated, with the capability of using its telemetry data for distributing them to all the members of the cooperative fleet, making it possible to access the real-time estimate of the states of each single drone, and making each one of them aware of the selected landing areas of the others, by navigation sensors data fusion with a five meters GPS precision.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127182952","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310833
E. Taşdelen, Volkan Sezer
Environment perception is a critical part of autonomous driving which is required to get a reliable and accurate object information from environment. LIDAR sensors are thought to be a key enabler for autonomous cars through their significant advantages on wide field-of-view and high-resolution capabilities. Automotive companies’ interest in LIDAR sensors is also thought to increase with slashed sensor prices over the years. Our main aim in this research is to get more precise object detection and tracking (ODT) system in real time for autonomous vehicles. In this paper, we have developed, applied and tested two different (low and high) realtime sensor fusion methods on multiple 3D LIDAR sensors for environment perception. The first contribution of this work is proposing and implementing “high level track-to-track fusion” method on multiple 3D LIDAR sensors. To the best of our knowledge, this is the first automotive application of track-to-track fusion method on multiple 3D LIDARs. Another contribution is the analysis and comparison of track-to-track fusion method performance with the well-studied low-level real-time fusion method. These two real-time fusion strategies are implemented in the experimental test truck which is instrumented with two 3D LIDAR sensors and the performance of the fusion strategies are tested under three different driving scenarios. Additionally, the ground truth data is collected with the help of global navigation satellite system (GNSS) in high accuracy for performance evaluation. The test results are analyzed in terms of defined performance criteria and the benefits & weaknesses of the proposed approach are discussed in this work.
{"title":"Comparison and Application of Multiple 3D LIDAR Fusion Methods for Object Detection and Tracking","authors":"E. Taşdelen, Volkan Sezer","doi":"10.1109/ICRAE50850.2020.9310833","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310833","url":null,"abstract":"Environment perception is a critical part of autonomous driving which is required to get a reliable and accurate object information from environment. LIDAR sensors are thought to be a key enabler for autonomous cars through their significant advantages on wide field-of-view and high-resolution capabilities. Automotive companies’ interest in LIDAR sensors is also thought to increase with slashed sensor prices over the years. Our main aim in this research is to get more precise object detection and tracking (ODT) system in real time for autonomous vehicles. In this paper, we have developed, applied and tested two different (low and high) realtime sensor fusion methods on multiple 3D LIDAR sensors for environment perception. The first contribution of this work is proposing and implementing “high level track-to-track fusion” method on multiple 3D LIDAR sensors. To the best of our knowledge, this is the first automotive application of track-to-track fusion method on multiple 3D LIDARs. Another contribution is the analysis and comparison of track-to-track fusion method performance with the well-studied low-level real-time fusion method. These two real-time fusion strategies are implemented in the experimental test truck which is instrumented with two 3D LIDAR sensors and the performance of the fusion strategies are tested under three different driving scenarios. Additionally, the ground truth data is collected with the help of global navigation satellite system (GNSS) in high accuracy for performance evaluation. The test results are analyzed in terms of defined performance criteria and the benefits & weaknesses of the proposed approach are discussed in this work.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130851944","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310805
Saber Kazeminasab, M. Aghashahi, M. Banks
Water distribution systems are critical infrastructure that are expected to supply healthy water. Deliberate or accidental incidents such as terrorist attacks or pipe breaks can contaminate potable water in pipelines. Inline mobile sensors are promising solutions which have been designed and developed to monitor water quality and detect leaks in water pipelines. These mobile sensors can move towards the location of contamination or leak and provide more timely and accurate measurements. However, these sensors, which are often free-swimming spheres and move by water flow, have two problems: instability and passiveness. In this research, we designed a robot that stabilizes and automates our previously fabricated spherical mobile sensor. The robot empowers a water utility operator to control the mobile sensor motion in a pressurized environment with a high-speed flow. The robot has three spring-based adjustable arms for stability in pipes with diameters between 22.86 (cm) — 9 (in) and 55.88 (cm) — 22 (in). Each arm is actuated with a motor and a wheel at its end. The wheels are in contact with a pipe wall, and the motors keep the robot moving. Each motor is customized with a gearhead that provides required torque at its wheel for motion. A lithium battery attached to the sphere supplies electricity for motors and sensors. The proposed design is characterized and prototyped in this paper. To evaluate the controllability and observability of the robot, we have linearized governing equations. Results show the successful performance of the robot in pipes.
{"title":"Development of an Inline Robot for Water Quality Monitoring","authors":"Saber Kazeminasab, M. Aghashahi, M. Banks","doi":"10.1109/ICRAE50850.2020.9310805","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310805","url":null,"abstract":"Water distribution systems are critical infrastructure that are expected to supply healthy water. Deliberate or accidental incidents such as terrorist attacks or pipe breaks can contaminate potable water in pipelines. Inline mobile sensors are promising solutions which have been designed and developed to monitor water quality and detect leaks in water pipelines. These mobile sensors can move towards the location of contamination or leak and provide more timely and accurate measurements. However, these sensors, which are often free-swimming spheres and move by water flow, have two problems: instability and passiveness. In this research, we designed a robot that stabilizes and automates our previously fabricated spherical mobile sensor. The robot empowers a water utility operator to control the mobile sensor motion in a pressurized environment with a high-speed flow. The robot has three spring-based adjustable arms for stability in pipes with diameters between 22.86 (cm) — 9 (in) and 55.88 (cm) — 22 (in). Each arm is actuated with a motor and a wheel at its end. The wheels are in contact with a pipe wall, and the motors keep the robot moving. Each motor is customized with a gearhead that provides required torque at its wheel for motion. A lithium battery attached to the sphere supplies electricity for motors and sensors. The proposed design is characterized and prototyped in this paper. To evaluate the controllability and observability of the robot, we have linearized governing equations. Results show the successful performance of the robot in pipes.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122990023","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310822
E. X. Wang, Xin Zhao, Yaqing Chen, Mei Liu, Ganlu Li, Min Ouyang, A. Liang
In this paper we present an automatic pulse taking robot for Traditional Chinese Medicine based on optimal designed Stewart platform. We first analyzed geometry of adult human wrists near pulse taking cun-guan-chi positions with an active stereo vision system to obtain a list of requirements for the robot. Then a seven degree-of-freedom Stewart platform is designed and optimized to match the requirements. With 3D printing and off-the-shelf parts, we developed a novel pulse taking robot that is capable of taking pulse data automatically, without any doctor’s intervention.
{"title":"Design of Pulse Diagnostic Robot for Traditional Chinese Medicine","authors":"E. X. Wang, Xin Zhao, Yaqing Chen, Mei Liu, Ganlu Li, Min Ouyang, A. Liang","doi":"10.1109/ICRAE50850.2020.9310822","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310822","url":null,"abstract":"In this paper we present an automatic pulse taking robot for Traditional Chinese Medicine based on optimal designed Stewart platform. We first analyzed geometry of adult human wrists near pulse taking cun-guan-chi positions with an active stereo vision system to obtain a list of requirements for the robot. Then a seven degree-of-freedom Stewart platform is designed and optimized to match the requirements. With 3D printing and off-the-shelf parts, we developed a novel pulse taking robot that is capable of taking pulse data automatically, without any doctor’s intervention.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131413384","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310879
Usman Ali, R. Hafiz, T. Tauqeer, U. Younis, Waqas Ali, Asrar Ahmad
Motor current signature analysis and vibration analysis techniques have been used for the identification and classification of faults in high power induction motors. Fast fourier transform has been applied to the time domain stator current signal and vibration signal of the induction motor. A comparison of the frequency spectrum has been performed between healthy and unhealthy motor current and vibration signals. Five different machine learning classification algorithms have been used to evaluate the performance of the induction motor. The developed system provides a cost-effective and real-time alternative to the conventional off-line induction motor condition monitoring systems.
{"title":"Towards Machine Learning based Real-time Fault Identification and Classification in High Power Induction Motors","authors":"Usman Ali, R. Hafiz, T. Tauqeer, U. Younis, Waqas Ali, Asrar Ahmad","doi":"10.1109/ICRAE50850.2020.9310879","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310879","url":null,"abstract":"Motor current signature analysis and vibration analysis techniques have been used for the identification and classification of faults in high power induction motors. Fast fourier transform has been applied to the time domain stator current signal and vibration signal of the induction motor. A comparison of the frequency spectrum has been performed between healthy and unhealthy motor current and vibration signals. Five different machine learning classification algorithms have been used to evaluate the performance of the induction motor. The developed system provides a cost-effective and real-time alternative to the conventional off-line induction motor condition monitoring systems.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132722974","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 : 2020-11-20DOI: 10.1109/icrae50850.2020.9310859
{"title":"ICRAE 2020 Cover Page","authors":"","doi":"10.1109/icrae50850.2020.9310859","DOIUrl":"https://doi.org/10.1109/icrae50850.2020.9310859","url":null,"abstract":"","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125279773","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310916
Sutirtha Chakraborty, J. Timoney
Human beings are principally efficient at synchronizing and predicting within a swiftly altering realtime environment. For instance, various activities that involve harmonized movements, like catching a ball and dancing, needs firm decision making, based on partial information. However, the synchronization of tasks offers serious difficulty for the current architecture of robots. This is even more difficult in Human-robot interactions. A potential solution is to consider all entities as coupled oscillators. Then, Kuramoto’s synchronous oscillator concept should then be applicable in an adaptive way. However, in real-life, uncertain sensory environments creates huge challenges. This paper reviews the progress of human robot synchronization for a musical performance. The results are presented in a quantitative manner. The paper provides a discussion of the research findings, along with an indication of the major future implications.
{"title":"Robot Human Synchronization for Musical Ensemble: Progress and Challenges","authors":"Sutirtha Chakraborty, J. Timoney","doi":"10.1109/ICRAE50850.2020.9310916","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310916","url":null,"abstract":"Human beings are principally efficient at synchronizing and predicting within a swiftly altering realtime environment. For instance, various activities that involve harmonized movements, like catching a ball and dancing, needs firm decision making, based on partial information. However, the synchronization of tasks offers serious difficulty for the current architecture of robots. This is even more difficult in Human-robot interactions. A potential solution is to consider all entities as coupled oscillators. Then, Kuramoto’s synchronous oscillator concept should then be applicable in an adaptive way. However, in real-life, uncertain sensory environments creates huge challenges. This paper reviews the progress of human robot synchronization for a musical performance. The results are presented in a quantitative manner. The paper provides a discussion of the research findings, along with an indication of the major future implications.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125280992","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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