Downwash-Aware Configuration Optimization for Modular Aerial Systems
Mengguang Li, Heinz Koeppl
AI summary
Problem
Modular aerial systems often ignore aerodynamic downwash interference in their design, causing efficiency loss and instability, while existing methods lack scalable ways to optimize 3D topologies under these physical constraints.
Approach
The framework enumerates non-isomorphic 3D connection topologies for homogeneous quadrotor modules, then solves a nonlinear optimization program to adjust connector angles and minimize control effort while enforcing collision-free downwash volume constraints.
Key results
- Scalable enumeration algorithm for non-isomorphic 3D module topologies
- Nonlinear optimization framework jointly tuning connector angles and control allocation under downwash constraints
- Validation via physics-based simulation and real-world experiments
- Demonstrated reduction in control input through compact, downwash-aware assemblies
Why it matters
Enables robust, task-adaptive modular aerial robots by bridging combinatorial assembly design with real-world aerodynamic constraints.
Abstract
This work proposes a framework that generates and optimally selects task-specific assembly configurations for a large group of homogeneous modular aerial systems, ex- plicitly enforcing bounds on inter-module downwash. Prior work largely focuses on planar layouts and often ignores aerodynamic interference. In contrast, firstly we enumerate non-isomorphic connection topologies at scale; secondly, we solve a nonlinear program to check feasibility and select the configuration that minimizes control input subject to actuation limits and downwash constraints. We evaluate the framework in physics-based simulation and demonstrate it in real-world experiments.