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论文:2020,Vol:38,Issue(5):977-986 |
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引用本文： |
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郭一聪, 刘小雄, 章卫国, 杨跃. 基于改进势场法的无人机三维路径规划方法[J]. 西北工业大学学报 |
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GUO Yicong, LIU Xiaoxiong, ZHANG Weiguo, YANG Yue. 3D Path Planning Method for UAV Based on Improved Artificial Potential Field[J]. Northwestern polytechnical university |
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| 基于改进势场法的无人机三维路径规划方法 |
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| 郭一聪, 刘小雄, 章卫国, 杨跃 |
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| 西北工业大学 自动化学院, 陕西 西安 710129 |
| 摘要: |
| 路径规划是无人机自主飞行的关键，考虑到采用传统人工势场法路径规划的不足，提出了一种人工势场法的改进优化算法并扩展到三维空间，以更好地实现在飞行约束下的无人机三维在线路径规划。该算法针对传统人工势场法中的目标不可达、易陷入局部最小、局部路径震荡等3个问题，进行了改进与优化。首先采用含相对距离的改进势场函数处理目标不可达问题，并提出了一种基于不同障碍或威胁模型最近点的优化斥力势场计算方法来优化路径；其次，针对易于陷入局部最小的问题，提出了一种设定启发式子目标点的方法；最后，针对局部路径的震荡问题，提出了利用记忆性合力的方法抑制震荡，改善路径规划效果。仿真结果表明，新算法有效克服了传统人工势场法的不足，在无人机三维在线路径规划中具有应用价值。 |
| 关键词:
无人机
路径规划
人工势场法
启发式子目标点
记忆合力
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| 3D Path Planning Method for UAV Based on Improved Artificial Potential Field |
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| GUO Yicong, LIU Xiaoxiong, ZHANG Weiguo, YANG Yue |
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| School of Automation, Northwestern Polytechnical University, Xi'an 710129, China |
| Abstract: |
| Path planning is the key technology for UAV to achieve autonomous flight. Considering the shortcomings of path planning based on the conventional potential field method, this paper proposes an improved optimization algorithm based on the artificial potential field method and extends it to three-dimensional space to better achieve flight constrained 3D online path planning for UAVs. The algorithm is improved and optimized aiming at the three problems of goal nonreachable with obstacle nearby (GNWON), easy to fall into local minimum, and path oscillation in traditional artificial potential field method. First, an improved potential field function with relative distance is used to solve the GNWON, and an optimized repulsive potential field calculation method based on different obstacles or threat models is proposed to optimize the planned path. Secondly, in order to make the drone jump out of the local minimum trap, a method of setting heuristic sub-target points is proposed. For local path oscillation, a method using memory sum force was proposed to improve the oscillation. The simulation results show that the improved optimization algorithm in this paper effectively makes up for the shortcomings of the traditional artificial potential field method, and the designed 3D online path planning algorithm for the UAV is practical and feasible. |
| Key words:
unmanned aerial vehicle (UAV)
path planning
artificial potential field
heuristic sub-target
memory force
optimization algorithm
simulation
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| 收稿日期: 2019-12-27
修回日期:
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| DOI: 10.1051/jnwpu/20203850977 |
| 基金项目: 国家自然科学基金（62073266）、航空科学基金（201905053003）与陕西省飞行控制与仿真技术重点实验室资助 |
| 通讯作者:
Email： |
| 作者简介: 郭一聪(1995-),西北工业大学博士研究生,主要从事飞行控制和路径规划研究。
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