DESIGN SISTEM KOMUNIKASI PADA SWARM ROBOT BERBASIS XBEE DENGAN TOPOLOGI JARINGAN MESH

Pada Penelitian Design Sistem komunikasi Pada Swarm Robot. Sistem komunikasi merupakan hal yang penting dalam swarm robot, karena perlunya koordinasi antar robot untuk berinteraksi dengan lingkungan. Koordinasi antar robot dalam menyelesaikan tugas yang diberikan dengan bertukar informasi. Pertukaran informasi dalam penelitian ini adalah informasi jarak antar robot dan jarak penghalang, serta arah gerak tujuan. Komunikasi antar robot ini menggunakan modul Zigbee dengan perangkat XBee. Pada pengujian ini topologi yang digunakan dalam sistem komunikasi adalah topologi jaringan mesh. Topologi jaringan mesh ini terdiri dari coordinator, router dan end device. Server bertindak sebagai coordinator untuk mengatur pertukaran informasi, serta robot sebagai router dan end device. Hasil pengujian ini didapatkan bahwa sistem komunikasi pada robot ini menghasilkan nilai RSSI (Receiver Strength Signal Indicator) semakin jauh jarak robot dengan koordinator maka semakin kecil nilai RSSI yang didapatkan dan berbanding terbalik ketika semakin dekat dengan robot maka semakin besar nilai RSSI yang didapat

Impact of initialization of a modified particle swarm optimization on cooperative source searching

Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environments and rigid searching constraints is an example of application where swarm robotics can be applied. Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. Improper parameter selection may lead to a premature convergence and thus robots will fail (i.e., low success rate) to locate the source within the given searching constraints. Additionally, target overshooting and improper initialization strategies may lead to a nonoptimal (i.e., take longer time to converge) target searching. In this study, a modified PSO and three different initializations strategies (i.e., random, equidistant and centralized) were proposed. The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. Additionally, the findings also indicate that the random initialization give better searching success compared to equidistant and centralize initialization

Decentralized Collision-Free Control of Multiple Robots in 2D and 3D Spaces

Decentralized control of robots has attracted huge research interests. However, some of the research used unrealistic assumptions without collision avoidance. This report focuses on the collision-free control for multiple robots in both complete coverage and search tasks in 2D and 3D areas which are arbitrary unknown. All algorithms are decentralized as robots have limited abilities and they are mathematically proved. The report starts with the grid selection in the two tasks. Grid patterns simplify the representation of the area and robots only need to move straightly between neighbor vertices. For the 100% complete 2D coverage, the equilateral triangular grid is proposed. For the complete coverage ignoring the boundary effect, the grid with the fewest vertices is calculated in every situation for both 2D and 3D areas. The second part is for the complete coverage in 2D and 3D areas. A decentralized collision-free algorithm with the above selected grid is presented driving robots to sections which are furthest from the reference point. The area can be static or expanding, and the algorithm is simulated in MATLAB. Thirdly, three grid-based decentralized random algorithms with collision avoidance are provided to search targets in 2D or 3D areas. The number of targets can be known or unknown. In the first algorithm, robots choose vacant neighbors randomly with priorities on unvisited ones while the second one adds the repulsive force to disperse robots if they are close. In the third algorithm, if surrounded by visited vertices, the robot will use the breadth-first search algorithm to go to one of the nearest unvisited vertices via the grid. The second search algorithm is verified on Pioneer 3-DX robots. The general way to generate the formula to estimate the search time is demonstrated. Algorithms are compared with five other algorithms in MATLAB to show their effectiveness