针对多机悬吊系统力位强耦合、传统算法避障失效、多目标优化难平衡的核心问题，提出运动耦合导向的力位协同避障规划方法。首先分析了多机悬吊系统的耦合特性，通过分步迭代协同求解策略求解多机耦合模型。其次构建了力位映射矩阵以描述张力与位置间的耦合关系，基于力学平衡原理建立了力位协同约束方程。然后提出了分层搜索与分步优化策略，将复杂问题分解为全局轨迹规划和局部力位优化两级子问题，实现了力位协同规划与避障的高效融合。然后设计了FLA-MGEA融合算法，MGEA（多策略间歇泉启发算法）通过引入混沌映射初始化、Lévy飞行寻优及稳定性约束条件，有效避免算法陷入局部最优；FLA（模糊逻辑算法）根据环境复杂度动态调整优化目标的权重。最后通过动态避障实验验证了该避障规划方法在力位协同精度及避障可靠性方面的性能，研究结果为混合驱动型悬吊系统的工程应用奠定了理论基础。

To address the core issues of strong coupling of force and position in multi-robot suspension systems, failure of traditional algorithms in obstacle avoidance, and difficulty in balancing multiple objectives in multi-objective optimization, a force-position collaborative obstacle avoidance planning method guided by motion coupling is proposed. Firstly, the coupling characteristics of the multi-robot suspension system are analyzed, and the multi-robot coupling model is solved by the stepwise iterative coordinated solution strategy. Secondly, the force-position mapping matrix is constructed to describe the coupling relationship between tension and position, and the force-position coordinated constraint equation is established based on the principle of mechanical equilibrium. Then, the hierarchical search and stepwise optimization strategy is proposed, which decomposes the complex problem into two sub-problems of global trajectory planning and local force-position optimization, achieving the efficient integration of force-position coordinated planning and obstacle avoidance. Then, the FLA-MGEA fusion algorithm is designed. MGEA (Multi-strategy Geyser-Inspired Algorithm) effectively avoids the algorithm falling into local optimum by introducing chaotic mapping initialization, Lévy flight optimization and stability constraint conditions; FLA (Fuzzy Logic Algorithm) dynamically adjusts the weight of the optimization objective according to the complexity of the environment. Finally, the dynamic obstacle avoidance experiment verifies the performance of the obstacle avoidance planning method in terms of force-position coordinated accuracy and obstacle avoidance reliability. The research results lay a theoretical foundation for the engineering application of the hybrid-drive suspension system.