Parrot Mambo Minidrone as a benchmark platform for low-cost UAV research: a review of control, autonomy, software validation, safety and experimental evaluation

Low-cost minidrone platforms are increasingly used in Unmanned Aerial Vehicle (UAV) research for safe indoor experimentation, controller development and engineering education. The Parrot Mambo Minidrone is particularly attractive because of its compact size, onboard sensing, MATLAB/Simulink compatibility and suitability for real-time validation. This review critically synthesises 137 studies published between 2018 and 2026 involving the Parrot Mambo, including studies where it appears alongside other UAV platforms. The literature spans modelling, state estimation, classical and intelligent control, robust nonlinear control, disturbance rejection, vision-based navigation, multi-UAV coordination, Human-Drone Interaction (HDI), software validation, cyber-resilience, education, safety analysis, energy-aware evaluation and hardware performance. A platform-centred taxonomy is developed to trace progression from Proportional-Integral-Derivative (PID)-based stabilisation toward adaptive, intelligent, perception-driven, software-aware and safety-conscious autonomy. PID and Proportional-Integral–Proportional-Derivative (PI-PD) controllers remain important baselines, while fuzzy-PID, Sliding Mode Control (SMC), Model Predictive Control (MPC), Model-Free Control (MFC), Reinforcement Learning (RL), Observer-Based Control (OBC) and Fault-Tolerant Control (FTC) address nonlinearities, disturbances, uncertainty and hardware constraints. However, software testing, cyber-resilience, fault diagnosis, reachability analysis, actuator health, aerodynamic constraints and energy-aware evaluation remain weakly integrated. The principal gap is the absence of a standardised benchmark jointly assessing control accuracy, robustness, perception reliability, energy use, computational load, software dependability, cyber-resilience, safety, actuator constraints and real-flight repeatability. Accordingly, this review proposes a benchmark-driven framework for integrated, safety-aware, hardware-aware and reproducible Parrot Mambo research.