MIGHTY: Hermite Spline-based Efficient Trajectory Planning

2025-11-13

AI Summary

Hard-constraint trajectory planning relies on commercial solvers and incurs high computational overhead; existing soft-constraint approaches often decouple spatiotemporal optimization or restrict the search space. This paper proposes an efficient Hermite-spline-based trajectory planning method that, for the first time, enables joint continuous-domain spatiotemporal optimization while fully exploiting the infinite-dimensional spline parameter space—thereby avoiding decoupling approximations and artificial constraints. The method employs gradient-based optimization to directly solve for parametric trajectory coefficients, enabling real-time replanning in dynamic environments. Simulation results demonstrate a 9.3% reduction in computation time, a 13.1% decrease in flight duration, and 100% task success rate compared to state-of-the-art methods. Physical experiments validate robust high-speed flight up to 6.7 m/s and sustained dynamic obstacle avoidance.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

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.

Problem

• Optimizes trajectories using Hermite splines for efficiency
• Reduces computation and travel time in motion planning
• Enables high-speed navigation in cluttered dynamic environments

Innovation

• Hermite spline-based spatiotemporal trajectory optimization
• Continuous search space fully leveraged for planning
• Achieves faster computation and reduced travel time