Zhang Zhihao, Liu Xiaodong, Feng Boyu
Air Traffic Control and Navigation College, Airforce Engineering University, Xi'an, China.
Equipment Management and UAV Engineering College, Airforce Engineering University, Xi'an, China.
Sci Rep. 2023 Sep 30;13(1):16453. doi: 10.1038/s41598-023-43783-7.
Obstacle avoidance path planning is considered an essential requirement for unmanned aerial vehicle (UAV) to reach its designated mission area and perform its tasks. This study established a motion model and obstacle threat model for UAVs, and defined the cost coefficients for evading and crossing threat areas. To solve the problem of obstacle avoidance path planning with full coverage of threats, the cost coefficients were incorporated into the objective optimization function and solved by a combination of Sequential Quadratic Programming and Nonlinear Programming Solver. The problem of path planning under threat full coverage with no solution was resolved by improving the Bézier curve algorithm. By introducing the dynamic threat velocity obstacle model and calculating the relative and absolute collision cones, a path planning algorithm under multiple dynamic threats was proposed to solve the difficulties of dynamic obstacle prediction and avoidance. Simulation results revealed that the proposed Through-out method was more effective in handling full threat coverage and dynamic threats than traditional path planning methods namely, Detour or Cross Gaps. Our study offers valuable insights into autonomous path planning for UAVs that operate under complex threat conditions. This work is anticipated to contribute to the future development of more advanced and intelligent UAV systems.
避障路径规划被认为是无人机到达指定任务区域并执行任务的一项基本要求。本研究建立了无人机的运动模型和障碍物威胁模型，并定义了规避和穿越威胁区域的成本系数。为解决威胁全覆盖下的避障路径规划问题，将成本系数纳入目标优化函数，并通过序列二次规划和非线性规划求解器相结合的方法进行求解。通过改进贝塞尔曲线算法解决了威胁全覆盖下无解的路径规划问题。通过引入动态威胁速度障碍模型并计算相对和绝对碰撞锥，提出了一种多动态威胁下的路径规划算法，以解决动态障碍物预测和规避的难题。仿真结果表明，所提出的贯穿式方法在处理全威胁覆盖和动态威胁方面比传统路径规划方法（即绕行或穿越间隙）更有效。我们的研究为在复杂威胁条件下运行的无人机自主路径规划提供了有价值的见解。这项工作有望为更先进、智能的无人机系统的未来发展做出贡献。
