为四轮独立转向机器人设计多模式路径规划，提升复杂环境适应性。
Hybrid A* Path Planning with Multi-Modal Motion Extension for Four-Wheel Steering Mobile Robots
- 在四维状态空间中融合运动模式，支持多种转向方式协同
- 引入多模式Reeds-Shepp曲线与智能模式切换策略，路径更平滑
- 适合需要高机动性的工业移动机器人场景
四轮独立转向（4WIS）系统赋予移动机器人丰富的运动模式，如阿克曼转向、侧向移动和平行移动，在狭窄环境中具备卓越的灵活性。然而，现有路径规划方法通常基于单一运动学模型，难以充分发挥4WIS平台的多模式能力。为此，本文提出一种扩展的Hybrid A*框架，运行于包含空间状态与运动模式的四维状态空间。该框架针对不同运动模式的运动学约束，设计了多模式Reeds-Shepp曲线；构建了考虑模式切换代价的增强启发式函数；并提出基于智能模式选择的终端连接策略，确保不同转向模式间的平滑过渡。所提规划器可在单条路径中无缝集成多种运动模式，显著提升4WIS机器人在复杂环境中的灵活性与适应性。实验结果表明，该方法在复杂环境下显著提升了路径规划性能。
原文摘要 · Abstract (English)
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.
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