π€ AI Summary
This study addresses the challenge of simultaneously achieving resilience and energy efficiency in hexacopters under single-propeller failure. The authors propose an optimization method based on variable airframe geometry, which enhances both fault tolerance and aerodynamic efficiency by adjusting the angle between adjacent propellers within a continuous configuration space. For the first time, experimental results demonstrate the existence of a geometrically feasible region that enables practical-level resilience without compromising energy efficiency, thereby overcoming traditional design trade-offs. Leveraging an open-source variable-geometry platform, an empirical power model, and an evaluation framework incorporating position accuracy and rotational kinetic energy, the developed Opti-Hexa prototype achieves stable hover under single-propeller failure while maintaining energy efficiency comparable to that of a standard star-shaped layout.
π Abstract
This work demonstrates experimentally the existence of a hexarotor prototype, termed Opti-Hexa, that simultaneously achieves practical resilience to single-propeller failures and energy efficiency comparable to a standard Star-shaped prototype with the same size, weight, hardware and software. Leveraging a novel open-source morphing platform, we investigate the trade-offs across a continuous range of geometries by varying the angles between adjacent propellers. We study practical efficiency through a data-fitted empirical power model and evaluate practical resilience by comparing the position accuracy and rotational kinetic energy during failure to those observed under nominal hovering conditions. Our experiments confirm the existence of a geometric viability region for this specific morphing platform, where resilience is ensured without the aerodynamic efficiency losses typically associated with practically resilient designs found in the state of the art. The complete hardware and software of the morphing platform are released to support further research.