287 research outputs found

    Optimal Motion Primitives for Multi-UAV Convoy Protection

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    (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Digital Object Identifier : 10.1109/ROBOT.2010.5509221In this paper we study the problem of controlling a number of Unmanned Aerial Vehicles (UAVs) to provide convoy protection to a group of ground vehicles. The UAVs are modeled as Dubins vehicles flying at a constant altitude with bounded turning radius. This paper first presents time-optimal paths for providing convoy protection to static ground vehicles. Then this paper addresses paths and control strategies to provide convoy protection to ground vehicles moving on a straight line. Minimum numbers of UAVs required to provide perpetual convoy protection for both cases are derived

    Optimal UAV Path Planning for Tracking a Moving Ground Vehicle with a Gimbaled Camera

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    This research develops a path planning algorithm that autonomously controls a UAV to provide convoy overwatch. The optimization algorithm determines the best path to y through developing a cost function that minimizes the control effort of the UAV and the deviation from a desired slant range. A heuristic-based algorithm was developed and implemented on the autopilot to approximate the optimal solution. In flight test, the UAV successfully tracked a moving ground vehicle by continually placing the UAV\u27s loiter point directly above the ground vehicle\u27s current location. This method was called the \follow-me mode and provided the baseline for real-world UAV convoy overwatch. The follow-me mode resulted in a cost function value that was 113 times greater than the optimal path. Through an in-depth analysis, the heuristic-based approach reduced this ratio down to only 7.5 times greater than the optimal path. The data collected shows tremendous promise for improving autonomous UAV performance through optimal control techniques

    A convoy protection strategy using the moving path following method

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    This paper considers the problem of convoy protection missions using a fixed-wing Unmanned Aerial Vehicle (UAV) in scenarios where the radius of the circular region of interest around the convoy is smaller than the UAV minimum turning radius. Using the Moving Path Following (MPF) method, we propose a guidance algorithmic strategy where a UAV moving at constant ground speed is required to converge to and follow a desired geometric moving path that is attached to the convoy center. Conditions under which the proposed strategy solves the convoy problem are derived. A performance metric that is proposed together with numerical simulation results demonstrate the effectiveness of the proposed approach.info:eu-repo/semantics/acceptedVersio

    Multi-UAV Convoy Protection: An Optimal Approach to Path Planning and Coordination

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    (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Digital Object Identifier : 10.1109/TRO.2010.2042325In this paper we study the problem of controlling a group of Unmanned Aerial Vehicles (UAVs) to provide convoy protection to a group of ground vehicles. The UAVs are modeled as Dubins vehicles flying at a constant altitude with bounded turning radius. We first present time-optimal paths for providing convoy protection to stationary ground vehicles. Then we propose a control strategy to provide convoy protection to ground vehicles moving on straight lines. The minimum number of UAVs required to provide perpetual convoy protection in both cases are derived

    3D Formation Control in Multi-Robot Teams Using Artificial Potential Fields

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    Multi-robot teams find applications in emergency response, search and rescue operations, convoy support and many more. Teams of autonomous aerial vehicles can also be used to protect a cargo of airplanes by surrounding them in some geometric shape. This research develops a control algorithm to attract UAVs to one or a set of bounded geometric shapes while avoiding collisions, re-configuring in the event of departure or addition of UAVs and maneuvering in mission space while retaining the configuration. Using potential field theory, weighted vector fields are described to attract UAVs to a desired formation. In order to achieve this, three vector fields are defined: one attracts UAVs located outside the formation towards bounded geometric shape; one pushes them away from the center towards the desired region and the third controls collision avoidance and dispersion of UAVs within the formation. The result is a control algorithm that is theoretically justified and verified using MATLAB which generates velocity vectors to attract UAVs to a loose formation and maneuver in the mission space while remaining in formation. This approach efficiently scales to different team sizes
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