Four-wheel independent steering (4WIS) systems provide mobile robots with a rich set of motion modes, such as Ackermann steering, lateral steering, and parallel movement, offering superior maneuverability in constrained environments. However, existing path planning methods generally assume a single kinematic model and thus fail to fully exploit the multi-modal capabilities of 4WIS platforms. To address this limitation, we propose an extended Hybrid A* framework that operates in a four-dimensional state space incorporating both spatial states and motion modes. Within this framework, we design multi-modal Reeds-Shepp curves tailored to the distinct kinematic constraints of each motion mode, develop an enhanced heuristic function that accounts for mode-switching costs, and introduce a terminal connection strategy with intelligent mode selection to ensure smooth transitions between different steering patterns. The proposed planner enables seamless integration of multiple motion modalities within a single path, significantly improving flexibility and adaptability in complex environments. Results demonstrate significantly improved planning performance for 4WIS robots in complex environments.

翻译：四轮独立转向系统为移动机器人提供了丰富的运动模式，例如阿克曼转向、横向转向和平行移动，在受限环境中展现出卓越的机动性。然而，现有路径规划方法通常基于单一运动学模型，未能充分利用四轮独立转向平台的多模态能力。为克服这一局限，我们提出一种扩展的混合A*框架，该框架在包含空间状态与运动模式的四维状态空间中运行。在此框架内，我们设计了适配各运动模式独特运动学约束的多模态Reeds-Shepp曲线，开发了考虑模式切换成本的增强启发函数，并引入具有智能模式选择的终端连接策略以确保不同转向模式间的平滑过渡。所提出的规划器能够在单一路径中无缝集成多种运动模态，显著提升了复杂环境下的灵活性与适应性。实验结果证明，该方法能显著提升四轮独立转向机器人在复杂环境中的规划性能。