Performance and energy consumption are fundamental to design and to implement embedded flight controllers for unmanned aerial vehicles. An important challenge faced by designers is to find the balance between performance, small size and energy consumption for the navigation system. Moreover, when the airship flights through unknown environments, conventional predefined routes are useless and more intelligent on-line route planning systems are required. This work evaluates the performance and energy consumption of a real time on-line route planner based on particle swarm optimization. The evaluation is carried out over performance restricted computation systems. In particular, we use 32 bit microcontroller systems, which are widely used in the automatic control of small unmanned aerial vehicles. Our results show that the implementation of a PSO algorithm for on-line route planning over a 32 bit microcontroller is feasible with execution times per PSO iteration between 5 and 54 seconds. Moreover, the energy consumption vary between 1 and 15 Joules per PSO iteration. A PSO iteration comprises the whole data processing to find the next advance point in the unknown region. We consider these results are quite promising in the sense that they show the feasibility of implementing complex optimization algorithm over performance restricted computer systems.