Qingji Gao

Collision free path planning based on region clipping for aircraft fuel tank inspection robot

Continuum robot has potential to run freely through a cluttered environment as aircraft fuel tank. To improve manual maintenance, we designed an aircraft fuel tank inspection robot which was composed of cable-driven sections. A suitable path is essential for the robot to reach the target zone while avoiding obstacles, but path planning for continuum robot is a challenge due to their complex kinematics models. To depict the collision free planning problem, a nonlinear, constrained optimization formulation was adopted. Projection strategy was presented and an imaginary straight line between the origin and the target was made up as a reference line to simplify the planning problem. We focused on the decrease of computing time complexity, and based on region clipping, a novel forward search method was proposed to solve this optimization-based planning problem. With the reference straight line, the minimum distance summation (MDS) was calculated to decide the optimal path relatively. Experiments on MATLAB were reasonably designed. Simulations and results analysis demonstrated excellent performance of region clipping search method and feasibility of the avoidance algorithm.

Application of Fuzzy Federal Kalman Filtering in the Airport Automatic Docking Guidance System

A novel method based on fuzzy federal Kalman filtering is presented, which is mainly used to improve the reliability of the airport automatic docking guidance system when measure values of sensors are fluctuated. If the measure values are fluctuated, the state vector covariance of each local filtering is modified by using the fuzzy inference system (FIS) to modify the weight of each fusion data online in main filtering, accordingly the disturbance of the fluctuation data is reduced. Experiment results proved that the algorithm was feasible to improve the reliability of the system.

Research of stability augmentation flight control algorithm for quadrotor unmanned air vehicles

To improve the flight stability of quadrotor unmanned air vehicles (UAVs) flight control problem, a stability augmentation controller design approach is presented under parameter variations and external disturbances. The controller is made of two parts: an inner-loop attitude controller and an outer-loop position controller. The inner-loop attitude controller is designed with backstepping algorithm. The outer-loop position controller is realized with fuzzy adaptive PID algorithm. The stability augmentation controller and its performance are evaluated using a non-linear, six degree of freedom (DOF) dynamic model of a quadrotor UAV in simulate and practical experiments. The results illustrate that the proposed controller can effectively realize the stability.

Set-point stabilization of nonholonomic mobile robot based on optimizing Bezier curve

The optimization algorithm of nonlinear controller based on cubic Bezier curve is presented. The nonholonomic mobile robot is stabilized to a desired pose, and the real-time planning and motion control is realized at the same time curvaturepsilas changing minimization is introduced to evaluate the Bezier curve. Using the penalty function method the problem of nonlinear constrained optimization is converted into unconstrained. Furthermore, the parameters of controller is optimized based on the improved Powell method. Simulation results is implemented on the VC++6.0 platform, and it was shown that the proposed approach is effective.