Wind Aware Batch Informed Trees for Path Planning of Small UAS to Minimize Travel Time
Battery capacity limits the endurance of small unmanned aerial systems (UAS). This paper presents a wind-aware extension of the Batch Informed Tree (BIT*) planner that exploits both ambient horizontal winds and thermal updrafts to reduce travel time. A wind-informed heuristic guides heading and airspeed adjustments while ensuring collision-free paths in cluttered environments. Experiments were conducted in both a 2D urban environment and a 3D cluttered environment with thermal updrafts to validate the approach. In simulations over these scenarios, travel-time reductions range from about 3.5 % under mild winds to as much as 25 % when strong updrafts are available, for only a 1.5 % increase in path length. These results illustrate how even modest wind fields can be leveraged to extend mission duration over kilometer-scale flights. A notable drawback is the increased computation time. A planning runs up to 70–80 times slower than a simple distance-minimizing strategy. Future work will aim to accelerate the planner and relax the requirement for perfect wind-field knowledge, moving toward real-time applicability.
Authors
- Seung-Keol Ryu (ORCID: https://orcid.org/0000-0001-5587-6809)
- Eric W. Frew (ORCID: https://orcid.org/0000-0003-3686-089X)
- Michael Moncton (ORCID: https://orcid.org/0009-0004-6972-256X)
- Han‐Lim Choi (ORCID: https://orcid.org/0000-0003-3985-0419)
- Myung‐Jin Jung (ORCID: https://orcid.org/0000-0002-5599-0705)
Institutions
- Korea Advanced Institute of Science and Technology (KR)
- University of Colorado Boulder (US)
- University of Colorado System (US)
Publication Details
- Published
- 2025-07-16
- DOI
- https://doi.org/10.2514/6.2025-3687
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00