Collaborative Sensing by Unmanned Aerial Vehicles
Collaborative Sensing by Unmanned Aerial Vehicles
  In many military and civilian applications, Unmanned Aerial Vehicles (UAVs) provide an indispensable platform for gathering information about the situation on the ground. In particular, they have the potential to revolutionize the way in which information is collected, fused and disseminated. These advantages are greatly enhanced if swarms of multiple UAVs are used, since this enables the collection of data from multiple vantage points using multiple sensors. However, enhancements to overall operational performance can be realised only if the platforms have a high degree of autonomy, which is achieved through machine intelligence. With this in mind, we report on our recently launched project, SUAAVE (Sensing, Unmanned, Autonomous, Aerial VEhicles), which seeks to develop and evaluate a fully automated sensing platform consisting of multiple UAVs. To achieve this goal, we will take a multiply disciplinary approach, focusing on the complex dependencies that exist between tasks such as data fusion, ad-hoc wireless networking, and multi-agent co-ordination. In this position paper, we highlight the related work in this area and outline our agenda for future work.
  UAV, UAV swarms, sensor networks, decentralized control
  13-16
  
    
      Teacy, W. T. L.
      
        5f962a10-9ab5-4b19-8016-cc72588bdc6a
      
     
  
    
      Nie, J.
      
        0670d81f-a71d-4c22-afc8-9c434f5a311d
      
     
  
    
      McClean, S.
      
        bbe010c3-4624-4e74-86d9-5153116478bb
      
     
  
    
      Parr, G.
      
        9f789a08-a087-4921-835e-b730e748e77a
      
     
  
    
      Hailes, S.
      
        83d9065c-0aef-4d68-a2fa-2cef8ed70683
      
     
  
    
      Julier, S.
      
        00f6cf7a-3065-4e02-a57b-803cf3814199
      
     
  
    
      Trigoni, N.
      
        f39900f6-29a6-4d0d-8667-1e2c0c3055f7
      
     
  
    
      Cameron, S.
      
        9088511e-751a-40ab-95e6-6548c3deae62
      
     
  
  
   
  
  
    
      May 2009
    
    
  
  
    
      Teacy, W. T. L.
      
        5f962a10-9ab5-4b19-8016-cc72588bdc6a
      
     
  
    
      Nie, J.
      
        0670d81f-a71d-4c22-afc8-9c434f5a311d
      
     
  
    
      McClean, S.
      
        bbe010c3-4624-4e74-86d9-5153116478bb
      
     
  
    
      Parr, G.
      
        9f789a08-a087-4921-835e-b730e748e77a
      
     
  
    
      Hailes, S.
      
        83d9065c-0aef-4d68-a2fa-2cef8ed70683
      
     
  
    
      Julier, S.
      
        00f6cf7a-3065-4e02-a57b-803cf3814199
      
     
  
    
      Trigoni, N.
      
        f39900f6-29a6-4d0d-8667-1e2c0c3055f7
      
     
  
    
      Cameron, S.
      
        9088511e-751a-40ab-95e6-6548c3deae62
      
     
  
       
    
 
  
    
      
  
  
  
  
    Teacy, W. T. L., Nie, J., McClean, S., Parr, G., Hailes, S., Julier, S., Trigoni, N. and Cameron, S.
  
  
  
  
   
    (2009)
  
  
    
    Collaborative Sensing by Unmanned Aerial Vehicles.
  
  
  
  
    
    
    
      
        
   
  
    the 3rd International Workshop on Agent Technology for Sensor Networks, Budapest, Hungary.
   
        
        
        
      
    
  
  
  
      
          
          
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      Record type:
      Conference or Workshop Item
      (Paper)
      
      
    
   
    
    
      
        
          Abstract
          In many military and civilian applications, Unmanned Aerial Vehicles (UAVs) provide an indispensable platform for gathering information about the situation on the ground. In particular, they have the potential to revolutionize the way in which information is collected, fused and disseminated. These advantages are greatly enhanced if swarms of multiple UAVs are used, since this enables the collection of data from multiple vantage points using multiple sensors. However, enhancements to overall operational performance can be realised only if the platforms have a high degree of autonomy, which is achieved through machine intelligence. With this in mind, we report on our recently launched project, SUAAVE (Sensing, Unmanned, Autonomous, Aerial VEhicles), which seeks to develop and evaluate a fully automated sensing platform consisting of multiple UAVs. To achieve this goal, we will take a multiply disciplinary approach, focusing on the complex dependencies that exist between tasks such as data fusion, ad-hoc wireless networking, and multi-agent co-ordination. In this position paper, we highlight the related work in this area and outline our agenda for future work.
         
      
      
        
          
            
  
    Text
 suaave.pdf
     - Accepted Manuscript
   
  
  
 
          
            
          
            
           
            
           
        
        
       
    
   
  
  
  More information
  
    
      Published date: May 2009
 
    
  
  
    
  
    
     
        Additional Information:
        Event Dates: May, 2009
      
    
  
    
     
        Venue - Dates:
        the 3rd International Workshop on Agent Technology for Sensor Networks, Budapest, Hungary, 2009-05-01
      
    
  
    
  
    
  
    
     
        Keywords:
        UAV, UAV swarms, sensor networks, decentralized control
      
    
  
    
     
        Organisations:
        Electronics & Computer Science
      
    
  
    
  
  
        Identifiers
        Local EPrints ID: 267290
        URI: http://eprints.soton.ac.uk/id/eprint/267290
        
        
        
        
          PURE UUID: 8f9959e9-571c-4650-a223-b7f72fbd4935
        
  
    
        
          
            
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
        
          
        
    
  
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  Date deposited: 23 Apr 2009 09:41
  Last modified: 14 Mar 2024 08:47
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      Contributors
      
          
          Author:
          
            
              
              
                W. T. L. Teacy
              
              
            
            
          
        
      
          
          Author:
          
            
            
              J. Nie
            
          
        
      
          
          Author:
          
            
            
              S. McClean
            
          
        
      
          
          Author:
          
            
            
              G. Parr
            
          
        
      
          
          Author:
          
            
            
              S. Hailes
            
          
        
      
          
          Author:
          
            
            
              S. Julier
            
          
        
      
          
          Author:
          
            
            
              N. Trigoni
            
          
        
      
          
          Author:
          
            
            
              S. Cameron
            
          
        
      
      
      
    
  
   
  
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