Method for Designating the Wind Condition in MDP-based Motion Planning of Under-actuated Blimp type UAV

Blimp-type unmanned aerial vehicles (BUAVs) does not consume any energy in keeping their longitudinal position in the air, so their use as a platform for mine searching missions is anticipated. For mine searching missions, a BUAV must fly near the ground. Because there is severe limitation on the weight of equipment, such as sensors and actuators, most BUAVs are so-called under-actuated robots. For a BUAV to fly near the ground safely, a sophisticated obstacle avoidance algorithm that considers the kinematical constraints of under-actuated BUAV is needed. In developing the obstacle avoidance algorithm for under actuated robot, establishing a motion planning method is essential. To carry out applicable motion planning calculation for a BUAV, detail information about the wind velocity condition and geometry of obstacles in the mission environment is needed; however, it is very difficult to accurately estimate wind velocity distribution that is disturbed by the obstacles. In this paper, a method for estimating a rough wind condition near the ground considering the geometrical property of obstacles is proposed. The estimated rough wind condition is applied to the stochastic motion planning calculation based on dynamic programming (DP) in Markov decision process (MDP). The performance of the method is examined by computational fluid dynamical (CFD) simulation.