Resumen:
This paper presents SANDO, a safe trajectory planner for 3D dynamic unknown environments. Existing soft- constraint planners are fast but do not guarantee collision-free paths, while hard-constraint methods typically ensure safety at the cost of longer computation. SANDO addresses this trade- off through three contributions. First, a heat map-based A global planner steers the path away from high-risk regions, and a spatiotemporal safe flight corridor (STSFC) generator produces time-layered polytopes that inflate obstacles only by their worst-case reachable set at each time layer, rather than over the entire horizon. Second, trajectory optimization is formulated as a mixed-integer quadratic program with hard collision-avoidance constraints, and variable elimination reduces the number of decision variables. Third, a formal safety anal- ysis establishes collision-free guarantees under explicit velocity- bound, size-bound, and estimation-error assumptions. Ablation studies confirm that variable elimination yields up to 7:4 × faster optimization and that STSFCs are critical for feasibility in dense dynamic environments. In simulations against state-of-the- art methods, SANDO achieves a 100% success rate across all forest and dynamic benchmark difficulty levels with no constraint violations, and perception-only experiments demonstrate the full perception-to-planning pipeline. Hardware experiments with fully onboard planning, perception, and localization demonstrate six safe flights in static environments and twelve among dynamic obstacles.
Resumen divulgativo:
SANDO es un sistema de navegación avanzado que permite a los drones volar rápidamente a través de entornos impredecibles y en movimiento sin estrellarse. Al predecir de manera inteligente los movimientos de los obstáculos y agilizar cálculos complejos, garantiza una trayectoria segura y libre de colisiones en tiempo real. Este avance demostró su seguridad tanto en intensas simulaciones como en pruebas de hardware en el mundo real.
Palabras Clave: Aerial systems: perception and autonomy, col lision avoidance, motion and path planning, optimization and optimal control.
Índice de impacto JCR-JIF y cuartil WoS: 11,100 - Q1 (2025)
Referencia DOI:
https://doi.org/10.1109/TRO.2026.3738474
In press: Septiembre 2026.
Cita:
K. Kondo, J. Tordesillas Torres, J. Rached, L. Sun, Y. Jia, J.P. How, "SANDO: Safe Autonomous Trajectory Planning for Dynamic Unknown Environments", IEEE Transactions on Robotics, doi: 10.1109/TRO.2026.3738474
