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基于虚拟力场的航天器集群重构轨迹规划方法

孙兆博1,丁学良2,吴宝林1,刘阳1,陈俊宇1   

  1. 1. 哈尔滨工业大学
    2. 中国航空工业集团公司成都飞机设计研究所
  • 收稿日期:2025-09-30 修回日期:2026-01-13 出版日期:2026-01-15 发布日期:2026-01-15
  • 通讯作者: 吴宝林
  • 基金资助:
    高端重载机器人全国重点实验室开放课题;空天飞行器技术航空科技重点实验室开放基金

A virtual force field-based trajectory planning method for spacecraft swarm reconfiguration

  • Received:2025-09-30 Revised:2026-01-13 Online:2026-01-15 Published:2026-01-15
  • Contact: Baolin WU

摘要: 对于大规模航天器集群的无碰撞构型控制任务,亟需快速生成安全的无碰撞转移轨迹。然而,直接求解包含复杂约束的轨迹规划问题很有挑战,尤其在集群成员数量较多的情况下,涉及碰撞规避约束的轨迹优化问题,其约束数量将随成员数量增长呈指数级增长。为此,本文提出了一种基于虚拟力场的直接轨迹优化算法。该算法通过设计具有共识性的虚拟力场,在空间几何层面对集群航天器的离散轨迹进行调整与优化,并结合航天器相对动力学的微分平坦特性,直接生成连续控制轨迹,从而避免了使用优化求解器处理复杂轨迹规划问题的需求。该方法的计算复杂度不受航天器集群规模的影响,能够通过虚拟力场的迭代过程生成近似最优、无碰撞风险的转移轨迹,克服了传统分布式轨迹优化算法中需频繁通信的缺点。此外,虚拟力场的生成过程具备解析形式,且满足共识性要求。与传统轨迹规划算法相比,该方法显著降低了计算资源消耗,同时确保了转移轨迹的近似最优性。仿真结果验证了所提出控制策略的有效性。

关键词: 航天器集群, 构形重构, 虚拟力场, 轨迹规划, 碰撞规避

Abstract: For the collision-free formation control of large-scale spacecraft swarms in space, it is essential to rapidly generate safe transfer trajectories that avoid collisions. However, directly solving trajectory planning problems with complex constraints is often impractical, especially when the swarm consists of a large number of agents. In such cases, the number of collision avoidance constraints increases exponentially with the swarm size, posing significant computational challenges. To address this issue, this paper proposes a direct trajectory optimization algorithm based on virtual force fields. By designing a consensus-driven virtual force field, the algorithm directly adjusts and optimizes the discrete trajectories of the swarm members at the geometric level. Leveraging the differentially flat characteristics of spacecraft relative dynamics, the method generates continuous control trajectories without relying on conventional optimization solvers for complex trajectory planning. The proposed approach maintains computational complexity independent of the swarm size. It iteratively constructs approximately optimal, collision-free transfer trajectories via virtual force field updates, thereby overcoming the heavy communication overhead typically required in traditional distributed trajectory optimization methods. Furthermore, the virtual force field is formulated analytically and ensures consensus across the swarm during each iteration. Compared to conventional trajectory planning algorithms, the proposed method significantly reduces computational resource consumption while preserving near-optimal trajectory quality. Simulation results validate the effectiveness of the proposed control strategy.

Key words: spacecraft swarm, formation reconfiguration, virtual force field, trajectory planning, collision avoidance

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