Flocking is defined as flying in groups without colliding into each other through data exchange where each UAV applies a decentralized algorithm. In this paper, hybrid flocking control is proposed by using three types of guidance methods: vector field, Cucker-Smale model, and potential field. Typically, hybrid flocking control using several methods can lead to generating conflicting commands and thus degrading the performance of the mission. To address this issue, the adaptive Cucker-Smale model is proposed. Besides, we use social learning particle swarm optimization to determine the optimal weightings between guidance methods. It is verified through numerical simulations that the optimal weighting for missions such as loitering and target tracking results in effective flocking.
{"title":"Decentralized Hybrid Flocking Guidance for a Swarm of Small UAVs","authors":"Seunghan Lim, Yeongho Song, Joonwon Choi, Hyun Myung, Heungsik Lim, H. Oh","doi":"10.1109/REDUAS47371.2019.8999710","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999710","url":null,"abstract":"Flocking is defined as flying in groups without colliding into each other through data exchange where each UAV applies a decentralized algorithm. In this paper, hybrid flocking control is proposed by using three types of guidance methods: vector field, Cucker-Smale model, and potential field. Typically, hybrid flocking control using several methods can lead to generating conflicting commands and thus degrading the performance of the mission. To address this issue, the adaptive Cucker-Smale model is proposed. Besides, we use social learning particle swarm optimization to determine the optimal weightings between guidance methods. It is verified through numerical simulations that the optimal weighting for missions such as loitering and target tracking results in effective flocking.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"330 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115379121","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999715
A. E. Gomez-Tamm, P. Ramón-Soria, B. Arrue, A. Ollero
Recently, several research has been developed to embed manipulators and actuators in Unmanned Aerial Vehicles (UAVs) to allow them to interact with the environment. However, there are strong limitations with these actuators which are mainly related with the weight and efficiency. This article reviews the state of art of bio-inspired solutions for aerial manipulators and presents cutting edge bio-inspired technologies that are potentially profitable in the field of aerial robotics.
{"title":"Current State and Trends on Bioinspired Actuators for Aerial Manipulation","authors":"A. E. Gomez-Tamm, P. Ramón-Soria, B. Arrue, A. Ollero","doi":"10.1109/REDUAS47371.2019.8999715","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999715","url":null,"abstract":"Recently, several research has been developed to embed manipulators and actuators in Unmanned Aerial Vehicles (UAVs) to allow them to interact with the environment. However, there are strong limitations with these actuators which are mainly related with the weight and efficiency. This article reviews the state of art of bio-inspired solutions for aerial manipulators and presents cutting edge bio-inspired technologies that are potentially profitable in the field of aerial robotics.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124227964","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 : 2019-11-01DOI: 10.1109/reduas47371.2019.8999669
{"title":"RED UAS 2019 Technical Program","authors":"","doi":"10.1109/reduas47371.2019.8999669","DOIUrl":"https://doi.org/10.1109/reduas47371.2019.8999669","url":null,"abstract":"","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122558828","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999689
C. W. Keong, Hyo-Sang Shin, A. Tsourdos
Effective collision avoidance strategy is crucial for the operation of any unmanned aerial vehicle. In order to maximise the safety and the effectiveness of the collision avoidance strategy, the strategy needs to solve for choosing the best action by taking account of any situation. In this paper, the traditional control method is replaced by a Reinforcement Learning (RL) method called Deep-Q-Network (DQN) and investigate the performance of DQN in aerial collision avoidance. This paper formulate the collision avoidance process as a Markov Decision Process (MDP). DQN will be trained in two simulated scenarios to approximate the best policy which will give us the best action for performing the collision avoidance. First simulation is head-to-head collision simulation following with head-to-head with a crossing aircraft simulation.
{"title":"Reinforcement Learning for Autonomous Aircraft Avoidance","authors":"C. W. Keong, Hyo-Sang Shin, A. Tsourdos","doi":"10.1109/REDUAS47371.2019.8999689","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999689","url":null,"abstract":"Effective collision avoidance strategy is crucial for the operation of any unmanned aerial vehicle. In order to maximise the safety and the effectiveness of the collision avoidance strategy, the strategy needs to solve for choosing the best action by taking account of any situation. In this paper, the traditional control method is replaced by a Reinforcement Learning (RL) method called Deep-Q-Network (DQN) and investigate the performance of DQN in aerial collision avoidance. This paper formulate the collision avoidance process as a Markov Decision Process (MDP). DQN will be trained in two simulated scenarios to approximate the best policy which will give us the best action for performing the collision avoidance. First simulation is head-to-head collision simulation following with head-to-head with a crossing aircraft simulation.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128754685","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 : 2019-11-01DOI: 10.1109/reduas47371.2019.8999698
{"title":"[Copyright notice]","authors":"","doi":"10.1109/reduas47371.2019.8999698","DOIUrl":"https://doi.org/10.1109/reduas47371.2019.8999698","url":null,"abstract":"","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130761128","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 : 2019-11-01DOI: 10.1109/REDUAS47371.2019.8999704
F. J. Garcia-Rubiales, P. Ramón-Soria, B. Arrue, A. Ollero
This article presents an automatic magnetic detaching system integrated in the perching mechanism of an Unmanned Aerial Vehicle. This system is prepared to be activated in emergencies, releasing the mechanism and letting the UAV to take off and fly away safely. This design has been particularly developed for using UAVs in the oil and gas industries. In these environments, emergencies are related to escapes of flammable gases. With the proposed design, the UAV can be aware of dangerous gas concentrations and escapes when it detects a rise in the level of these gases. All the power is held in the UAV, so the perching system remains mechanically stable but without dangerous power sources.
{"title":"Magnetic detaching system for Modular UAVs with perching capabilities in industrial environments","authors":"F. J. Garcia-Rubiales, P. Ramón-Soria, B. Arrue, A. Ollero","doi":"10.1109/REDUAS47371.2019.8999704","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999704","url":null,"abstract":"This article presents an automatic magnetic detaching system integrated in the perching mechanism of an Unmanned Aerial Vehicle. This system is prepared to be activated in emergencies, releasing the mechanism and letting the UAV to take off and fly away safely. This design has been particularly developed for using UAVs in the oil and gas industries. In these environments, emergencies are related to escapes of flammable gases. With the proposed design, the UAV can be aware of dangerous gas concentrations and escapes when it detects a rise in the level of these gases. All the power is held in the UAV, so the perching system remains mechanically stable but without dangerous power sources.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131178869","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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