用赫尔米特样条实现高效时空联合规划，兼顾速度与成功率。
MIGHTY: Hermite Spline-based Efficient Trajectory Planning
- 基于赫尔米特样条的连续空间优化，统一处理位置与时间维度。
- 仿真中计算时间减少9.3%，行程时间缩短13.1%，成功率100%。
- 适合高速动态避障场景，硬件验证支持6.7m/s飞行。
硬约束轨迹规划通常依赖商业求解器，需大量计算资源。现有软约束方法虽加快计算速度，但或分离空间与时间优化，或限制搜索空间。为此，我们提出MIGHTY，一种基于赫尔米特样条的规划器，在充分利用样条连续搜索空间的同时实现时空联合优化。仿真中，MIGHTY相比当前最优基线，计算时间减少9.3%，行程时间缩短13.1%，成功率100%。硬件实验中，MIGHTY成功完成多个最高达6.7 m/s的高速飞行任务，覆盖杂乱静态环境及动态添加障碍物的长时间飞行场景。
原文摘要 · Abstract (English)
Hard-constraint trajectory planners often rely on commercial solvers and demand substantial computational resources. Existing soft-constraint methods achieve faster computation, but either (1) decouple spatial and temporal optimization or (2) restrict the search space. To overcome these limitations, we introduce MIGHTY, a Hermite spline-based planner that performs spatiotemporal optimization while fully leveraging the continuous search space of a spline. In simulation, MIGHTY achieves a 9.3% reduction in computation time and a 13.1% reduction in travel time over state-of-the-art baselines, with a 100% success rate. In hardware, MIGHTY completes multiple high-speed flights up to 6.7 m/s in a cluttered static environment and long-duration flights with dynamically added obstacles.
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