The path planning process for an unmanned aerial vehicle is a complex process due to different operating environment conditions and aircraft constraints. The particle swarm optimization algorithm is one of several heuristic techniques used to solve the path planning problem. However, it has been observed that this algorithm tends to converge prematurely to a local optimum, resulting in poor quality paths. This paper proposes an adaptive strategy for calculating the inertia weight (KPSO) of the particles in the PSO algorithm for UAV path planning in a real-world environment. The strategy was applied to a reconnaissance mission during an eruptive event based on the Popocatepetl volcano area in Mexico and was found to outperform other adaptive strategies from the literature in a specific scenario.

In this work we develop a mathematical model to estimate the error for inverse kinematics problem for Gough-Stewart parallel mechanisms. We propose the estimation error method to include manufacture, assembly, backlash, and sensing errors. We provide the error transmission matrices for the length of each leg of the hexapod, which permits evaluation of the accuracy error in the position of each one, given a desired position and orientation of the mobile platform. We also present numerical modelling in order to estimate the accuracy of the methodology herein proposed, for specific attitude operations corresponding to performing a successful ground-LEO nanosatellite optical link. In such a case, we were able to provide the required tolerances for the actuators in order to guarantee an orientation precision requirement of the order of milliradians.

This paper presents a systemic model for the simulation of the design of a nozzle for R-Candy. This research is focused on a complex system using the methodology of 5 phases based on the tools of systemic modeling and general systems theory. The rocket motor was designed using Solidworks, which consists of the igniter system, the combustion chamber, and the nozzle. Usually, a Laval-type nozzle (convergent-divergent) is used for rocket motors, taking advantage of the exothermic properties of the potassium nitrate and sorbitol fuel mixture in a solid state. The simulation was carried out using the computational fluid dynamics software FEATool, evaluating temperature, velocity, and pressure. The results obtained by the R-Candy software give guidelines for a broad preliminary panorama for the manufacture of rocket motors in experimental rocketry.