抄録
Recently, it is expected to develop an autonomous robot working in a living environment. Motion planning is very important for an autonomous mobile robot, but kinematic constraints and dynamic constraints are generally solved separately in conventional motion planning. In this research, a simpler way of deciding the control input for an autonomous mobile robot, which is described by a highly nonlinear model in a multi-dimensional space, is proposed by solving kinematic constraints and dynamic constraints simultaneously, under the kinodynamic motion planning based on a harmonic potential field (HPF). In this paper, a quadrotor that is very attractive as an aerial robot due to its high maneuverability, is assumed to be a controlled object, and it is aimed at guiding the quadrotor to an arbitrary target point while avoiding obstacles. Then, three types of controllers for kinodynamic motion planning based on an HPF, which were developed for point mass control, are extended to be applied to the quadrotor. The extended controllers are compared each other in trajectory, amplitude of attitude, and arrival time through some flight simulations. Moreover, multiple gains included in the proposed controllers are optimized automatically by using genetic algorithm (GA), in order to realize highly accurate control. Flight simulation in an untrained environment, which is different from the environment that the gains were selected by GA, is also conducted, and it is confirmed that the quadrotor can move onto the target point with the same gains while avoiding obstacles.
