MIGHTY: Hermite spline-based efficient trajectory planning

Aerospace Controls Lab researchers have developed algorithms that let small flying robots quickly figure out safe paths through cluttered, changing environments. The new planning method (MIGHTY) helps drones jointly decide both where and how fast to travel, enabling successful real-world tests at speeds up to 6.7 m/s.

Authors: Kota Kondo, Yuwei Wu, Vijay Kumar, and Jonathan How
Citation: IEEE Robotics and Automation Letters, 2025

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.

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.