In recent years, the demand for adaptable unmanned aerial vehicles (UAVs) has surged, particularly for multirotor drones that can handle diverse payloads and operational environments. Traditional fixed-configuration multirotor drones often fall short in scenarios requiring rapid reconfiguration for varying load capacities or spatial constraints. To address this, I propose a modular assembly strategy utilizing octagonal truss lattice structures, which combines lightweight, high-strength properties with customizable functionality. This approach enables the construction of multirotor drones through discrete, standardized modules, allowing for dynamic adjustments in size, configuration, and performance. In this article, I detail the design methodology, mechanical analysis, and practical implementation of such a modular multirotor drone, supported by simulations and real-world testing. The goal is to demonstrate how lattice-based modularity can enhance the versatility and efficiency of multirotor drones in complex applications.
The core of this strategy lies in decomposing the drone’s structure into reusable octagonal truss lattice unit cells. Each unit cell is designed with standardized bolt holes at its nodes, facilitating easy assembly and disassembly. The geometric parameters of the unit cell, such as strut width and thickness, are optimized to maintain structural integrity while allowing for parametric adjustments. For instance, the dimensions at reinforced connection points follow specific relationships to ensure compatibility and strength. The relative density of the unit cell, a key factor influencing mechanical properties, can be expressed as:
$$ \frac{\rho}{\rho_S} = 32 \left( \frac{b t}{L^2} \right) \left[ 1 + 6.39 \left( \frac{b}{L} \right) – 2.59 \left( \frac{t}{L} \right) \right] $$
where \( \rho \) is the density of the unit cell, \( \rho_S \) is the material density, \( b \) is the strut width, \( t \) is the strut thickness, and \( L \) is the cell edge length. This equation allows for precise control over the unit cell’s mass and stiffness, enabling tailored designs for specific multirotor drone requirements. By varying these parameters, I can achieve desired specific stiffness and strength, which scale with relative density as power-law functions:
$$ \frac{E}{E_S} \propto \left( \frac{\rho}{\rho_S} \right)^a, \quad \frac{\sigma}{\sigma_S} \propto \left( \frac{\rho}{\rho_S} \right)^b $$
Here, \( E \) and \( \sigma \) represent the effective elastic modulus and strength of the lattice, while \( E_S \) and \( \sigma_S \) are those of the base material. Constants \( a \) and \( b \) are derived from finite element simulations and experimental data, typically ranging between 1 and 2 for octagonal truss lattices. This relationship underscores the flexibility of the modular approach, as I can optimize unit cells for high load-bearing capacity or minimal weight, depending on the multirotor drone’s intended use.
Assembly of these unit cells into larger structures involves bolted connections at each face, with five bolt holes per surface ensuring robust, multi-directional expansion. The bolt hole positions are strategically placed near nodes to minimize stress concentrations and maintain the lattice’s inherent mechanical properties. The required bolt length and hole dimensions are determined by:
$$ e \geq \frac{\max\{M, m\}}{2} + \max\{H, h\}, \quad 2t + h \leq L_b \leq e – \frac{D}{2} $$
where \( e \) is the edge distance, \( M \) and \( m \) are the nut and bolt head diameters, \( H \) and \( h \) are their thicknesses, \( D \) is the bolt hole diameter, and \( L_b \) is the bolt length. This standardization ensures that modules can be rapidly assembled into various multirotor drone configurations, such as quadcopters, hexacopters, and octocopters, by combining full unit cells with half-cells or hybrid cells. For example, a quadcopter arm might comprise a 1x1xn array of unit cells, where \( n \) determines the arm length and, consequently, the propeller size and thrust capacity. The maximum propeller diameter \( d_{\text{max}} \) relates to the drone’s radius \( D \) and number of arms \( n \) by:
$$ d_{\text{max}} = D \sin \left( \frac{180^\circ}{n} \right) $$
To minimize aerodynamic interference, the actual propeller diameter \( d_p \) should satisfy \( d_{\text{max}} = 1.05d_p \) to \( 1.2d_p \), allowing for efficient thrust generation in multirotor drones. This modularity not only facilitates size scaling but also enables the creation of complex geometries, such as tilted arms for overlapping propeller planes, which enhance lift without increasing the overall footprint.
| Parameter | Value |
|---|---|
| Density (kg/m³) | 1240 |
| Elastic Modulus (MPa) | 2400 |
| Poisson’s Ratio | 0.4 |
| Strength Limit (MPa) | 34 |
To validate the mechanical performance of the unit cells, I conducted finite element simulations and experimental tests under quasi-static compression. The unit cells were fabricated using fused deposition modeling (FDM) with PLA basic material, whose properties are summarized in Table 1. Simulations in ABAQUS employed a hexahedral mesh and an elastoplastic material model, while experiments used an INSTRON 5966 testing machine at a strain rate of \( 5 \times 10^{-4} \, \text{s}^{-1} \). The stress-strain curves from both methods showed strong agreement, with elastic behavior up to 4% strain, followed by plastic yielding and eventual fracture. The effective stress \( \sigma \) and strain \( \varepsilon \) are defined as:
$$ \sigma = \frac{F}{S_0} = \frac{F}{l_0^2}, \quad \varepsilon = \frac{\Delta l}{l_0} = \frac{l_0 – l}{l_0} $$
where \( F \) is the applied force, \( S_0 \) is the initial cross-sectional area, \( l_0 \) is the original length, and \( \Delta l \) is the displacement. These results confirm that the unit cells exhibit predictable mechanical behavior, essential for reliable performance in multirotor drones. However, 3D-printed defects, such as layer separation, can reduce post-yield strength, highlighting the importance of design margins in practical applications.
When multiple unit cells are assembled into larger structures, size effects become significant. I analyzed the compression behavior of assemblies with varying numbers of unit cells, keeping \( L = 100 \, \text{mm} \), \( b = 4 \, \text{mm} \), and \( t = 4 \, \text{mm} \). As the assembly size increases, stiffness slightly improves due to a lower proportion of under-constrained boundary struts, but strength decreases marginally because of heightened stress concentrations from increased constraints. This trade-off necessitates careful consideration in multirotor drone design, especially for arms subjected to bending and torsion. The bending and torsional stiffness of arms composed of \( n \) unit cells decrease asymptotically with \( n \), primarily due to the cumulative compliance of bolted connections. For instance, in a multirotor drone with long arms, a ring configuration may be preferable to a cross layout to maintain sufficient rigidity against vibrations, which are critical for flight stability.
| Parameter | Value |
|---|---|
| Body Diameter (with Propellers) (mm) | 2100 |
| Body Height (mm) | 500 |
| Wheelbase (mm) | 1500 |
| Empty Weight (kg) | 18 |
| Design Payload (kg) | 10 |
| Maximum Takeoff Weight (kg) | 54 |
| Motor Model | Hobbywing X6Plus |
| Propeller Model | Hobbywing 24*8 |
| Maximum Thrust per Axis (kg) | 11.8 |
| Battery Model | LiPo 12S-45.6V-25C-16000mAh |
| Estimated Endurance (min) | 15 |
Applying this modular strategy, I designed a meter-scale octocopter multirotor drone with a ring configuration and tilted arms to maximize propeller size and thrust. The drone’s overall parameters are listed in Table 2. The frame consists of 98 full unit cells and 40 half-cells, assembled with bolts, and includes custom units for motor attachment. Component selection was guided by software tools like Flyeval, ensuring compatibility with off-the-shelf parts. The structural integrity was verified through finite element analysis using inertia relief methods to simulate free-flight conditions. Under maximum takeoff weight, the loads include self-weight, external payload, propeller thrust, and torque, as detailed in Table 3. The stress distribution showed a maximum von Mises stress of 16.88 MPa, below the allowable stress of 22.67 MPa (considering a safety factor of 1.5), while arm deflections were limited to 11.93 mm, corresponding to a 1.75° bend, indicating adequate stiffness for stable flight of the multirotor drone.
| Load Type | Application Method | Magnitude |
|---|---|---|
| Self-Weight | Gravity | 18 kg × G |
| External Payload | Gravity (Point Mass) | 36 kg × G |
| Propeller Thrust | Concentrated Force | 1180 N × 8 |
| Propeller Torque | Concentrated Moment | 29.5 N·m × 8 |
| Inertial Forces | Inertia Relief | Satisfies Equilibrium |
Modal analysis of the multirotor drone frame revealed natural frequencies below \( 1 \times 10^{-3} \) Hz for the first 30 modes, with dominant modes in the vertical direction. The effective mass participation was over 99.999%, confirming that resonant vibrations from propeller rotations (typically above 10 Hz) are unlikely. This ensures that the modular structure remains stable during operation, a crucial aspect for multirotor drones relying on precise attitude control. The assembly process involved manually bolting the modules together, followed by integrating motors, batteries, and flight control systems. Outdoor flight tests demonstrated stable hover and maneuverability, validating the design’s practicality. The modular multirotor drone successfully carried its design payload, with flight times aligning with predictions, underscoring the efficacy of the lattice-based approach.
In conclusion, the modular assembly of multirotor drones using octagonal truss lattices offers significant advantages in customization, scalability, and performance. By leveraging parametric unit cells and standardized connections, I achieved a versatile platform that adapts to various mission profiles. The mechanical properties of the lattices, governed by relative density and size effects, enable tailored designs for specific needs, while simulations and tests confirm structural reliability. Future work could explore advanced materials, such as carbon-fiber composites, to enhance strength-to-weight ratios, or automated assembly techniques for rapid deployment. This strategy not only extends the capabilities of multirotor drones but also paves the way for innovative applications in logistics, surveillance, and environmental monitoring, where adaptability is paramount. The success of this modular multirotor drone underscores the potential of discrete lattice structures in advancing UAV technology.