The Experts below are selected from a list of 31983 Experts worldwide ranked by ideXlab platform
John Vian - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Indoor Autonomous Vehicle Test Environment
IEEE Control Systems, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:To investigate and develop unmanned vehicle systems technologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called real-time indoor autonomous vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a controlled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultaneously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternatively, RAVEN provides a facility for Testing low-level control algorithms on both fixed- and rotary-wing aerial platforms. RAVEN is also being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
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Real-Time Indoor Autonomous Vehicle Test Environment: A TestBED FOR THE RAPID PROTOTYPING OF UNMANNED VEHICLE TECHNOLOGIES
IEEE CONTROL SYSTEMS MAGAZINE, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:U nmanned aerial vehicles (UAVs) are becoming vital warfare and homeland-security platforms because they significantly reduce costs and the risk to human life while amplifying warfighter and first-responder capabilities. These vehicles have been used in Iraq and during Hurricane Katrina rescue efforts with some success, but there remains a formidable barrier to achieving the vision of multiple UAVs operating cooperatively. Numerous researchers are investigating systems that use multiple autonomous agents to cooperatively execute these missions [1]–[4]. However, little has been said to date about how to perform multiday autonomous system operations. Autonomous mission systems must balance vehicle capability, reliability, and robustness issues with task and mission goals when creating an effective strategy. In addition, these systems have the added responsibility of interacting with numerous human operators while managing both high-level mis-sion goals and individual tasks. To investigate and develop unmanned vehicle systems tech-nologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called Real-time indoor Autonomous Vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a con-trolled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultane-ously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternative-ly, RAVEN provides a facility for Testing low-level control algo-rithms on both fixed-and rotary-wing aerial platforms. RAVEN is also Digital Object Identifier 10.1109/MCS.2007.914691 1066-033X/08/$25.00©2008IEEE APRIL 2008 « IEEE CONTROL SYSTEMS MAGAZINE 51 being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
Jonathan P. How - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Indoor Autonomous Vehicle Test Environment
IEEE Control Systems, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:To investigate and develop unmanned vehicle systems technologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called real-time indoor autonomous vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a controlled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultaneously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternatively, RAVEN provides a facility for Testing low-level control algorithms on both fixed- and rotary-wing aerial platforms. RAVEN is also being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
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Real-Time Indoor Autonomous Vehicle Test Environment: A TestBED FOR THE RAPID PROTOTYPING OF UNMANNED VEHICLE TECHNOLOGIES
IEEE CONTROL SYSTEMS MAGAZINE, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:U nmanned aerial vehicles (UAVs) are becoming vital warfare and homeland-security platforms because they significantly reduce costs and the risk to human life while amplifying warfighter and first-responder capabilities. These vehicles have been used in Iraq and during Hurricane Katrina rescue efforts with some success, but there remains a formidable barrier to achieving the vision of multiple UAVs operating cooperatively. Numerous researchers are investigating systems that use multiple autonomous agents to cooperatively execute these missions [1]–[4]. However, little has been said to date about how to perform multiday autonomous system operations. Autonomous mission systems must balance vehicle capability, reliability, and robustness issues with task and mission goals when creating an effective strategy. In addition, these systems have the added responsibility of interacting with numerous human operators while managing both high-level mis-sion goals and individual tasks. To investigate and develop unmanned vehicle systems tech-nologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called Real-time indoor Autonomous Vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a con-trolled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultane-ously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternative-ly, RAVEN provides a facility for Testing low-level control algo-rithms on both fixed-and rotary-wing aerial platforms. RAVEN is also Digital Object Identifier 10.1109/MCS.2007.914691 1066-033X/08/$25.00©2008IEEE APRIL 2008 « IEEE CONTROL SYSTEMS MAGAZINE 51 being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
D Dale - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Indoor Autonomous Vehicle Test Environment
IEEE Control Systems, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:To investigate and develop unmanned vehicle systems technologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called real-time indoor autonomous vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a controlled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultaneously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternatively, RAVEN provides a facility for Testing low-level control algorithms on both fixed- and rotary-wing aerial platforms. RAVEN is also being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
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Real-Time Indoor Autonomous Vehicle Test Environment: A TestBED FOR THE RAPID PROTOTYPING OF UNMANNED VEHICLE TECHNOLOGIES
IEEE CONTROL SYSTEMS MAGAZINE, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:U nmanned aerial vehicles (UAVs) are becoming vital warfare and homeland-security platforms because they significantly reduce costs and the risk to human life while amplifying warfighter and first-responder capabilities. These vehicles have been used in Iraq and during Hurricane Katrina rescue efforts with some success, but there remains a formidable barrier to achieving the vision of multiple UAVs operating cooperatively. Numerous researchers are investigating systems that use multiple autonomous agents to cooperatively execute these missions [1]–[4]. However, little has been said to date about how to perform multiday autonomous system operations. Autonomous mission systems must balance vehicle capability, reliability, and robustness issues with task and mission goals when creating an effective strategy. In addition, these systems have the added responsibility of interacting with numerous human operators while managing both high-level mis-sion goals and individual tasks. To investigate and develop unmanned vehicle systems tech-nologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called Real-time indoor Autonomous Vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a con-trolled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultane-ously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternative-ly, RAVEN provides a facility for Testing low-level control algo-rithms on both fixed-and rotary-wing aerial platforms. RAVEN is also Digital Object Identifier 10.1109/MCS.2007.914691 1066-033X/08/$25.00©2008IEEE APRIL 2008 « IEEE CONTROL SYSTEMS MAGAZINE 51 being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
Brett Bethke - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Indoor Autonomous Vehicle Test Environment
IEEE Control Systems, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:To investigate and develop unmanned vehicle systems technologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called real-time indoor autonomous vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a controlled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultaneously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternatively, RAVEN provides a facility for Testing low-level control algorithms on both fixed- and rotary-wing aerial platforms. RAVEN is also being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
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Real-Time Indoor Autonomous Vehicle Test Environment: A TestBED FOR THE RAPID PROTOTYPING OF UNMANNED VEHICLE TECHNOLOGIES
IEEE CONTROL SYSTEMS MAGAZINE, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:U nmanned aerial vehicles (UAVs) are becoming vital warfare and homeland-security platforms because they significantly reduce costs and the risk to human life while amplifying warfighter and first-responder capabilities. These vehicles have been used in Iraq and during Hurricane Katrina rescue efforts with some success, but there remains a formidable barrier to achieving the vision of multiple UAVs operating cooperatively. Numerous researchers are investigating systems that use multiple autonomous agents to cooperatively execute these missions [1]–[4]. However, little has been said to date about how to perform multiday autonomous system operations. Autonomous mission systems must balance vehicle capability, reliability, and robustness issues with task and mission goals when creating an effective strategy. In addition, these systems have the added responsibility of interacting with numerous human operators while managing both high-level mis-sion goals and individual tasks. To investigate and develop unmanned vehicle systems tech-nologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called Real-time indoor Autonomous Vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a con-trolled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultane-ously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternative-ly, RAVEN provides a facility for Testing low-level control algo-rithms on both fixed-and rotary-wing aerial platforms. RAVEN is also Digital Object Identifier 10.1109/MCS.2007.914691 1066-033X/08/$25.00©2008IEEE APRIL 2008 « IEEE CONTROL SYSTEMS MAGAZINE 51 being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
Adrian Frank - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Indoor Autonomous Vehicle Test Environment
IEEE Control Systems, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:To investigate and develop unmanned vehicle systems technologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called real-time indoor autonomous vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a controlled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultaneously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternatively, RAVEN provides a facility for Testing low-level control algorithms on both fixed- and rotary-wing aerial platforms. RAVEN is also being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
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Real-Time Indoor Autonomous Vehicle Test Environment: A TestBED FOR THE RAPID PROTOTYPING OF UNMANNED VEHICLE TECHNOLOGIES
IEEE CONTROL SYSTEMS MAGAZINE, 2008Co-Authors: Jonathan P. How, Adrian Frank, Brett Bethke, D Dale, John VianAbstract:U nmanned aerial vehicles (UAVs) are becoming vital warfare and homeland-security platforms because they significantly reduce costs and the risk to human life while amplifying warfighter and first-responder capabilities. These vehicles have been used in Iraq and during Hurricane Katrina rescue efforts with some success, but there remains a formidable barrier to achieving the vision of multiple UAVs operating cooperatively. Numerous researchers are investigating systems that use multiple autonomous agents to cooperatively execute these missions [1]–[4]. However, little has been said to date about how to perform multiday autonomous system operations. Autonomous mission systems must balance vehicle capability, reliability, and robustness issues with task and mission goals when creating an effective strategy. In addition, these systems have the added responsibility of interacting with numerous human operators while managing both high-level mis-sion goals and individual tasks. To investigate and develop unmanned vehicle systems tech-nologies for autonomous multiagent mission platforms, we are using an indoor multivehicle Testbed called Real-time indoor Autonomous Vehicle Test Environment (RAVEN) to study long-duration multivehicle missions in a con-trolled Environment. Normally, demonstrations of multivehicle coordination and control technologies require that multiple human operators simultane-ously manage flight hardware, navigation, control, and vehicle tasking. However, RAVEN simplifies all of these issues to allow researchers to focus, if desired, on the algorithms associated with high-level tasks. Alternative-ly, RAVEN provides a facility for Testing low-level control algo-rithms on both fixed-and rotary-wing aerial platforms. RAVEN is also Digital Object Identifier 10.1109/MCS.2007.914691 1066-033X/08/$25.00©2008IEEE APRIL 2008 « IEEE CONTROL SYSTEMS MAGAZINE 51 being used to analyze and implement techniques for embedding the fleet and vehicle health state (for instance, vehicle failures, refueling, and maintenance) into UAV mission planning. These characteristics facilitate the rapid prototyping of new vehicle configurations and algorithms without requiring a redesign of the vehicle hardware. This article describes the main components and architecture of RAVEN and presents recent flight Test results illustrating the applications discussed above.
