Three Dimensional Obstacle Avoidance of Autonomous Blimp Flying in Unknown Disturbance

A blimp-type unmanned aerial vehicle (BUAV) maintains its longitudinal motion using buoyancy provided by the air around it. This means the density of a BUAV equals that of the surrounding air. Because of this, the motion of a BUAV is seriously affected by flow disturbances, whose distribution is usually non-uniform and unknown. In addition, the inertia in the heading motion is very large. There is also a strict limitation on the weight of equipment in the BUAV, so most BUAVs are so-called under-actuated robots. From this situation, it can be said that the motion planning of the BUAV considering the stochastic property of the disturbance is needed for obstacle avoidance. In this paper, we propose an approach to the motion planning of the BUAV via the application of Markov decision process (MDP). The proposed approach consists of a method to prepare a discrete MDP model of the BUAV motion and a method to maintain the effect of the unknown wind on the BUAVs motion. The performance of the methods is examined by dynamical simulation of the BUAV in the environment with wind disturbance

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