Applying the Quantum Approximate Optimization Algorithm to the UAV Collision Avoidance Problem - Santos, Kalleb C.; Vianna, Maria Eduarda W. M.; Oliveira, Mateus K. de; Rosa, Evandro Chagas Ribeiro da; Panisson, Alison R.; Bittencourt, Luiz F.; Rodrigues-Filho, Roberto (Anais do Simpósio Brasileiro de Computação e Comunicação Quânticas (SBCCQ), 2026)
The increasing availability of quantum hardware has stimulated interest in applying quantum algorithms to combinatorial optimization problems. Collision avoidance for unmanned aerial vehicles (UAVs) is one such challenge due to the computational complexity of coordinating multiple agents in shared airspace. In this paper, we formulate the problem as a Quadratic Unconstrained Binary Optimization (QUBO) model that captures route selection and collision constraints, enabling the use of the Quantum Approximate Optimization Algorithm (QAOA). To improve efficiency, we introduce a constrained QAOA Ansatz employing an XY-mixer that preserves one-hot route assignment constraints and restricts the search space to valid solutions. We evaluate the approach through noiseless simulations and device-based noise models, analyzing its behavior under realistic conditions and highlighting the opportunities and limitations of near-term quantum hardware for multi-agent routing problems.