TITLE:
Multi-UAV Path Planning and Collision Avoidance: Algorithms and Emerging Trends
AUTHORS:
Husayn Merchant, Sananjay Biswas
KEYWORDS:
Multi-UAV Systems, Cooperative Path Planning, Collision Avoidance, Trajectory Optimization, Safety-Critical Control, Multi-Agent Learning
JOURNAL NAME:
World Journal of Engineering and Technology,
Vol.14 No.4,
October
19,
2026
ABSTRACT: Multi-UAV routing requires integration of route planning, time-separation, vehicle dynamics, sensing and communication uncertainties, and computational resources onboard. This critical review provides a comparison of graph search, multi-agent path finding, sampling, optimization, reactive control, safety filters, and multi-agent learning techniques in terms of explicit assumptions and types of evidence supporting their use. Optimization techniques allow generating dynamically feasible trajectories only when the underlying dynamics and constraints are correctly modeled, and a solution is found by the solver; initialization, nonconvexity, and computation may preclude this possibility. Reactive approaches provide fast empirical reaction, yet can experience deadlock problems, whereas learned policies are still hard to certify beyond test environments. We separate guarantees derived from assumptions, conditional properties, and empirical results and contrast multi-UAV flights and simulations to transferable evidence. Specification of the search strategy and audit of the selected literature reveal limitations of the selection process. Our review identifies calibrated safety margins and a practical benchmark for testing collision avoidance and liveness in multi-UAV systems.