Abstract
The unknown two-dimensional obstacles, including different shapes, numbers, locations, and in the vicinity of the planning path for an outdoor quadrotor, are on-line detected by a 360-degree Li-Dar Sweep Scanse. Based on the comparison among detected triangles containing extreme points of each obstacle, the central orientation of the triangle with the maximum detected distance and the angle larger than the specific threshold is assigned to fly a specific distance for obstacle avoidance. Nevertheless, the quadrotor probably encounters a dead end and is then navigated to a specific altitude for the continuous procedure of obstacle detection. By on-line detection at different waypoints for the same obstacle, an obstacle mapping is also established by all the obstacle detections. Since the sensing signals of an outdoor quadrotor are easily affected by stochastic noise and the quadrotor is operated in “x” configuration, an extended Kalman filter based fuzzy tracking incremental control (EKF-FTIC) is employed to simultaneously execute the path tracking, obstacle avoidance, and target approach. Finally, the experiments with 5 unknown obstacles in the neighborhood of a planning path connecting start point with end point validate the effectiveness and feasibility of the proposed method.
Highlights
There has been increasing interest in quadrotor unmanned aerial vehicles (QUAVs) with autonomous navigation capabilities so that they can rapidly and safely fly through complex environments [1]–[15]
The trajectory tracking control of an outdoor UAV is difficult since more sensors (e.g., GPS and inertial navigation system) are required and stochastic disturbances are often
The unknown obstacles include different shapes, numbers, and locations. They are in the neighbor of the planned path of an outdoor quadrotor and on-line detected by 360-degree Sweep Scanse [33]
Summary
There has been increasing interest in quadrotor unmanned aerial vehicles (QUAVs) with autonomous navigation capabilities so that they can rapidly and safely fly through complex environments [1]–[15]. Given the environment perception and vehicle state estimation, the on- line path planner generates smooth and safe trajectories from a start point to a target point in the configuration space, while avoiding unexpected obstacles during the navigation. Most of these papers are for the indoor quadrotor [1]–[7]; some papers are only theoretical studies [8], [9], [14], [15]. The unknown obstacles include different shapes, numbers, and locations They are in the neighbor of the planned path of an outdoor quadrotor and on-line detected by 360-degree Sweep Scanse [33]. Together with the suitable covariance matrices of the EKF ([3], [34]) and the tuning mechanism of the FTIC (the coefficients of sliding surface, the scaling factors, and the fine tuning in the fuzzy table), the satisfactory control performance (without the risk of a larger change of the control input’s amplitude, and the simultaneous path tracking and obstacle avoidance) are achieved [16]
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