A Novel Dual Quaternion Based Dynamic Motion Primitives for Acrobatic Flight
This addresses the challenge of motion description for fixed-wing UAV acrobatic flight, which is incremental as it builds on imitation learning and dynamic motion primitives.
The paper tackles the problem of describing acrobatic flight maneuvers for fixed-wing UAVs by proposing a dual quaternion-based dynamic motion primitives (DQ-DMP) method that combines position and attitude states without accuracy loss, with simulation results showing superiority over traditional decoupling methods.
The realization of motion description is a challenging work for fixed-wing Unmanned Aerial Vehicle (UAV) acrobatic flight, due to the inherent coupling problem in ranslational-rotational motion. This paper aims to develop a novel maneuver description method through the idea of imitation learning, and there are two main contributions of our work: 1) A dual quaternion based dynamic motion primitives (DQ-DMP) is proposed and the state equations of the position and attitude can be combined without loss of accuracy. 2) An online hardware-inthe-loop (HITL) training system is established. Based on the DQDMP method, the geometric features of the demonstrated maneuver can be obtained in real-time, and the stability of the DQ-DMP is theoretically proved. The simulation results illustrate the superiority of the proposed method compared to the traditional position/attitude decoupling method.