UNMANNED AIR VEHICLE PATH PLANNING FOR MARITIME SURVEILLANCE USING CLUSTER-BASE METHOD

This paper discusses a method to determine the operation route for unmanned aerial vehicles for maritime surveillance. It is well known that there are several methods to make an aircraft path planning for ground related missions. On the other hand, path planning for maritime purposes is unnoticeable. The major problem of path planning for maritime is the abundant number of nodes which can make the route becomes quite long. Hence, reducing the number of nodes is necessary to rectify this problem. The main method is to separate the surveillance area into a smaller area of operation using clustering methods and then analyze the vulnerable area using the database to create an optimum flight path in each operation area. Although this paper specifically addresses a maritime-related mission, the path planning procedures can be applied to other missions as well. In this research, the input is given from satellite recorded data. Natuna Sea is chosen as the main discussion as the Natuna Sea currently is one of the most vulnerable regions in Indonesia for illegal fishing activity. The result shows that the aircraft path able to cover most of the vulnerable areas while optimizing the route distance.

Design, Assembly and Testing of a Mobile Laboratory Based on a VTOL Scale Motorglider

The objective of this paper is to explain the design steps and performance analysis of a vertical take-off and landing (VTOL) unmanned air vehicle (UAV) based on a Pilatus B4 glider scale model. Energy consumption, forces and thrust analyses are carry out to determinate the perfect match between low take-off weight and high aerodynamic performance. As a first approach a complete analysis of glider aerodynamic performances are settle to understand and design a proper support for VTOL conversion. Longitudinal static stability is fulfilled by evaluating the center of gravity location with respect to neutral position, nevertheless dynamic stability, and V-n diagram in VTOL configuration are evaluated to guarantee a correct behavior during fixed wing flight mode. In addition, power requirements, motor thrust capability and tilt-motors servo assisted system performance are determinate in perspective of flight performance to find out the perfect transition from multirotor take-off and landing mode to fixed-wing flying state. For these purposes a test bench has being designed to evaluate thrust, electrical absorption and rpm motor behavior along the throttle range. Finally, the assembly and preliminary tests are performed in order to validate the VTOL and Forward flight capability.

Aerodynamic design and optimization of propellers for multirotor

Purpose This paper aims to present a methodology of designing a custom propeller for specified needs. The example of propeller design for large unmanned air vehicle (UAV) is considered. Design/methodology/approach Starting from low fidelity Blade Element (BE) methods, the design is obtained using evolutionary algorithm-driven process. Realistic constraints are used, including minimum thickness required for stiffness, as well as manufacturing ones – including leading and trailing edge limits. Hence, the interactions between propellers in hex-rotor configuration, and their influence on structural integrity of the UAV are investigated. Unsteady Reynolds-Averaged Navier–Stokes (URANS) are used to obtain loading on the propeller blades in hover. Optimization of the propeller by designing a problem-specific airfoil using surrogate modeling-driven optimization process is performed. Findings The methodology described in the current paper proved to deliver an efficient blade. The optimization approach allowed to further improve the blade efficiency, with power consumption at hover reduced by around 7%. Practical implications The methodology can be generalized to any blade design problem. Depending on the requirements and constraints the result will be different. Originality/value Current work deals with the relatively new class of design problems, where very specific requirements are put on the propellers. Depending on these requirements, the optimum blade geometry may vary significantly.

Hear-and-avoid for unmanned air vehicles using convolutional neural networks

To investigate how an unmanned air vehicle can detect manned aircraft with a single microphone, an audio data set is created in which unmanned air vehicle ego-sound and recorded aircraft sound are mixed together. A convolutional neural network is used to perform air traffic detection. Due to restrictions on flying unmanned air vehicles close to aircraft, the data set has to be artificially produced, so the unmanned air vehicle sound is captured separately from the aircraft sound. They are then mixed with unmanned air vehicle recordings, during which labels are given indicating whether the mixed recording contains aircraft audio or not. The model is a convolutional neural network that uses the features Mel frequency cepstral coefficient, spectrogram or Mel spectrogram as input. For each feature, the effect of unmanned air vehicle/aircraft amplitude ratio, the type of labeling, the window length and the addition of third party aircraft sound database recordings are explored. The results show that the best performance is achieved using the Mel spectrogram feature. The performance increases when the unmanned air vehicle/aircraft amplitude ratio is decreased, when the time window is increased or when the data set is extended with aircraft audio recordings from a third party sound database. Although the currently presented approach has a number of false positives and false negatives that is still too high for real-world application, this study indicates multiple paths forward that can lead to an interesting performance. Finally, the data set is provided as open access.