Multi-objective Evolution of Drone Morphology

TL;DR

This paper uses evolutionary algorithms to optimize drone body designs for different objectives, revealing novel morphologies that outperform standard quadcopters in specific performance metrics.

Contribution

It introduces a multi-objective evolutionary approach to drone design, identifying optimal morphologies for thrust, maneuverability, and size, surpassing traditional quadcopters.

Findings

Evolved drone bodies outperform standard quadcopters in at least one objective.

Significant improvements in maneuverability, thrust-to-weight ratio, and size.

Different optimal designs depend on specific performance trade-offs.

Abstract

The design of multicopter drones has remained almost the same since its inception. While conventional designs, such as the quadcopter, work well in many cases, they may not be optimal in specific environments or missions. This paper revisits rotary drone design by exploring which body morphologies are optimal for different objectives and constraints. Specifically, an evolutionary algorithm is used to produce optimal drone morphologies for three objectives: (1) high thrust-to-weight ratio, (2) high maneuverability, and (3) small size. To generate a range of optimal drones with performance trade-offs between them, the non-dominated sorting genetic algorithm II, or NSGA-II is used. A randomly sampled population of 600 is evolved over 2000 generations. The NSGA-II algorithm evolved drone bodies that outperform a standard 5-inch 220 mm wheelbase quadcopter in at least one of the three objectives. The three extrema in the Pareto front show improvement of 487.8%, 23.5% and 4.8% in maneuverability, thrust-to-weight ratio and size, respectively. The improvement in maneuverability can be attributed to the tilt angles of the propellers, while the increase in thrust-to-weight ratio is primarily due to the higher number of propellers. The quadcopter is located on the Pareto front for the three objectives. However, our results also show that other designs can be better depending on the objectives.