MIGHTY: Hermite Spline-based Efficient Trajectory Planning
Kondo, Kota, Wu, Yuwei, Kumar, Vijay, How, Jonathan P.
–arXiv.org Artificial Intelligence
Abstract-- 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. T o 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. Trajectory planning for autonomous navigation has been extensively studied, with a wide variety of parameterizations and formulations [3], [6], [7], [9], [12], [14]-[17], [19]-[23].
arXiv.org Artificial Intelligence
Dec-8-2025
- Country:
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- Shaanxi Province > Xi'an (0.04)
- North America > United States
- Massachusetts > Middlesex County
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- Massachusetts > Middlesex County
- Asia > China
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