73 resultados para Unmanned Aerial Vehicle (UAV)


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Trajectory optimization of a generic launch vehicle is considered in this paper. The trajectory from launch point to terminal injection point is divided in to two segments. The first segment deals with launcher clearance and vertical raise of the vehicle. During this phase, a nonlinear feedback guidance loop is incorporated to assure vertical raise in presence of thrust misalignment, centre of gravity offset, wind disturbance etc. and possibly to clear obstacles as well. The second segment deals with the trajectory optimization, where the objective is to ensure desired terminal conditions as well as minimum control effort and minimum structural loading in the high dynamic pressure region. The usefulness of this dynamic optimization problem formulation is demonstrated by solving it using the classical Gradient method. Numerical results for both the segments are presented, which clearly brings out the potential advantages of the proposed approach.

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In this paper, we present the design and development details of a micro air vehicle (MAV) built around a quadrotor configuration. A survey of implemented MAVs suggests that a quadrotor design has several advantages over other configurations, especially in the context of swarm intelligence applications. Our design approach consists of three stages. However, the focus of this paper is restricted to the first stage that involves selection of crucial components such as motor-rotor pair, battery source, and structural material. The application of MAVs are broad-ranging, from reconnaissance to search and rescue, and have immense potential in the rapidly advancing field of swarm intelligence.

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A multiple UAV search and attack mission in a battlefield involves allocating UAVs to different target tasks efficiently. This task allocation becomes difficult when there is no communication among the UAVs and the UAVs sensors have limited range to detect the targets and neighbouring UAVs, and assess target status. In this paper, we propose a team theoretic approach to efficiently allocate UAVs to the targets with the constraint that UAVs do not communicate among themselves and have limited sensor range. We study the performance of team theoretic approach for task allocation on a battle field scenario. The performance obtained through team theory is compared with two other methods, namely, limited sensor range but with communication among all the UAVs, and greedy strategy with limited sensor range and no communication. It is found that the team theoretic strategy performs the best even though it assumes limited sensor range and no communication.

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The report talks about the implementation of Vehicle Detection tool using opensource software - WxPython. The main functionality of this tool includes collection of data, plotting of magnetometer data and the count of the vehicles detected. The report list about how installation process and various functionality of the tool.

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The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.