Visual Sensor System Applied to Trajectory Generation for UAVs

Mendoza, Luis Felipe Muñoz; Bonilla, José Trinidad Guillen; García–Torales, Guillermo; Lúa, Cuauhtémoc Acosta; Gennaro, S. Di

doi:10.1109/ropec55836.2022.10018749

Cited by 1 publication

(1 citation statement)

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“…Motors 1 and 3 rotate counterclockwise, while motors 2 and 4 rotate clockwise, with respect to the z-axis of the body frame B, each with an angular velocity ω j ≥ 0, generating thrust forces f j for j ∈ 1, 2, 3, 4 in free air. For a detailed and comprehensive dynamic model of the quadrotor, including the equations governing its motion, please refer to [27,[36][37][38][39].…”

Section: Quadrotor Dynamic Modelmentioning

confidence: 99%

Quadrotor Trajectory Control Based on Energy-Optimal Reference Generator

Bianchi,

Borri,

Cappuzzo

et al. 2024

Drones

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Inspired by the limited battery life of multi-rotor unmanned aerial vehicles (UAVs), this research investigated hierarchical real-time control of UAVs with the generation of energy-optimal reference trajectories. The goal was to design a reference generator and controller based on optimal-control theory that would guarantee energy consumption close to optimal with lower computational cost. First, a least-squares-estimation-(LSE) algorithm identified the parameters of the UAV mathematical model. Then, by considering a precise electrical model for the brushless DC motors and rest-to-rest maneuvers, the extraction of clear rules to compute the optimal mission time and generate ’energetic trajectories’ was performed. These rules emerged from analyzing the optimal-control strategy results that minimized the consumption over many simulations. Afterward, a hierarchical controller tracked those desired energetic trajectories identified as sub-optimal. Numerical experiments compared the results regarding trajectory tracking, energy performance index, and battery state of charge (SOC). A co-simulation framework consisting of commercial software tools, Simcenter Amesim for the physical modeling of the UAV, and Matlab-Simulink executed numerical simulations of the implemented controller.

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