In the UAV path planning study, due to the relative movement of multiple targets and the UAV, long-term and large-scale UAV, autonomous tracking has not been achieved. Therefore, aiming at this problem, this paper uses radar to provide a real-time feedback on target position, estimates the later motion state of the target according to its position, and then perform dynamic path planning by combining the feedback data and the state estimation result. Finally, The UAV path is optimized in real time. Experiments show that the proposed scheme can better plan the UAV path when multiple targets are in motion, thus improving the intelligence of the UAV and the capability of long time tracking.

Joint clearances inevitably affect the kinematic accuracy and robustness of landing gear retraction mechanisms. However, the complexity and uncertainty of the clearances lead to difficulty in establishing mathematic models and analyzing effects. In the interest of assessing the clearance effects on the kinematic accuracy of landing gears, an integrated tolerance theory is proposed in this paper. In the theory proposed, Jacobian–Torsor model is combined with robust analysis to establish the kinematic accuracy model and predict the influences of clearances. The overall steps to apply the theory presented in practice are given. A typical landing gear retraction mechanism is chosen for the case study and the results show that the tendencies of clearances can be observed. Through the process of tolerance design, robust study, and tolerance redesign, the kinematic accuracy is significantly improved. The integrated tolerance theory proposed and the study conducted will provide designers new insights for the clearance analysis of landing gear mechanisms.