Studi Performansi Algoritma Perencanaan Jalur diantara PRM, RRT, RRT* dan Informed-RRT

This paper will discuss a comparative performance review of several path planning algorithms. This study compares five well-known path planning algorithms, namely the Probabilistic Roadmap (PRM), Rapidly-exploring Random Tree (RRT), RRT* and Informed-RRT* algorithm. Testing is done through simulation based experiments using python. The test was conducted using several existing benchmark cases, namely narrow, maze, trap and clutter environment. The optimality criteria compared are path costs, computational time and the total number of nodes in the tree needed. The results of this study will provide information to readers about which algorithm is most suitable for use in user applications where there are several working parameters to be optimized. The findings have been summarized in the conclusion section. Keywords ­: Motion planning, PRM, RRT, RRT*, Informed-RRT*Makalah ini akan membahas tinjauan perbandingan performansi dari beberapa algoritma perencanaan jalur. Penelitian ini membandingkan empat algoritma perencanaan jalur yang terkenal, yaitu algoritma Probabilistic Roadmap (PRM), Rapidly-exploring Random Tree (RRT), RRT* dan Informed-RRT*. Pengujian dilakukan melalui eksperimen berbasis simulasi menggunakan python. Pengujian dilakukan menggunakan beberapa kasus benchmark yang ada, yaitu lingkungan narrow, maze, trap dan clutter. Kriteria optimalitas yang dibandingkan adalah biaya jalur, waktu komputasi dan jumlah total node pada pohon yang dibutuhkan. Hasil penelitian ini akan memberikan informasi kepada pembaca mengenai algoritma mana yang paling cocok untuk digunakan pada aplikasi pengguna dimana terdapat beberapa parameter kerja yang hendak dioptimalkan. Temuan telah diringkas pada bagian kesimpulan.  Kata Kunci : Perencanaan jalur, PRM, RRT, RRT*, Informed-RRT

Wireless coverage using unmanned aerial vehicles

The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civilian application domains including real-time monitoring, search and rescue, and wireless coverage. UAVs can be used to provide wireless coverage during emergency cases where each UAV serves as an aerial wireless base station when the cellular network goes down. They can also be used to supplement the ground base station in order to provide better coverage and higher data rates for the users. During such situations, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. Given the recharging requirements, the problem of minimizing the number of UAVs required for a continuous coverage of a given area is first studied in this dissertation. Due to the intractability of the problem, partitioning the coverage graph into cycles that start at the charging station is proposed and the minimum number of UAVs to cover such a cycle is characterized based on the charging time, the traveling time and the number of subareas to be covered by a cycle. Based on this analysis, an efficient algorithm is proposed to solve the problem. In the second part of this dissertation, the problem of optimal placement of a single UAV is studied, where the objective is to minimize the total transmit power required to provide wireless coverage for indoor users. Three cases of practical interest are considered and efficient solutions to the formulated problem under these cases are presented. Due to the limited transmit power of a UAV, the problem of minimizing the number of UAVs required to provide wireless coverage to indoor users is studied and an efficient algorithm is proposed to solve the problem. In the third part of this dissertation, the problem of maximizing the indoor wireless coverage using UAVs equipped with directional antennas is studied. The case that the UAVs are using one channel is considered, thus in order to maximize the total indoor wireless coverage, the overlapping in their coverage volumes is avoided. Two methods are presented to place the UAVs; providing wireless coverage from one building side and from two building sides. The results show that the upside-down arrangements of UAVs can improve the total coverage by 100% compared to providing wireless coverage from one building side. In the fourth part of this dissertation, the placement problem of UAVs is studied, where the objective is to determine the locations of a set of UAVs that maximize the lifetime of wireless devices. Due to the intractability of the problem, the number of UAVs is restricted to be one. Under this special case, the problem is formulated as a convex optimization problem under a restriction on the coverage angle of the ground users and a gradient projection based algorithm is proposed to find the optimal location of the UAV. Based on this, an efficient algorithm is proposed for the general case of multiple UAVs. The problem of minimizing the number of UAVs required to serve the ground users such that the time duration of uplink transmission of each wireless device is greater than or equal to a threshold value is also studied. Two efficient methods are proposed to determine the minimum number of UAVs required to serve the wireless devices