10 citations · 33 across the 33 of their papers we have counts for
6 papers · 1 filter
Modeling Aggregate Downwash Forces for Dense Multirotor Flight
Jennifer Gielis, Ajay Shankar, Ryan Kortvelesy +1
Dense formation flight with multirotor swarms is a powerful, nature-inspired flight regime with numerous applications in the realworld. However, when multirotors fly in close verti…
On the Trade-Off between Stability and Representational Capacity in Graph Neural Networks
Zhan Gao, Amanda Prorok, Elvin Isufi
Analyzing the stability of graph neural networks (GNNs) under topological perturbations is key to understanding their transferability and the role of each architecture component. H…
BenchMARL: Benchmarking Multi-Agent Reinforcement Learning
Matteo Bettini, Amanda Prorok, Vincent Moens
The field of Multi-Agent Reinforcement Learning (MARL) is currently facing a reproducibility crisis. While solutions for standardized reporting have been proposed to address the is…
Docking Multirotors in Close Proximity using Learnt Downwash Models
Ajay Shankar, Heedo Woo, Amanda Prorok
Unmodeled aerodynamic disturbances pose a key challenge for multirotor flight when multiple vehicles are in close proximity to each other. However, certain missions \textit{require…
SO(2)-Equivariant Downwash Models for Close Proximity Flight
H. Smith, A. Shankar, J. Gielis +2
Multirotors flying in close proximity induce aerodynamic wake effects on each other through propeller downwash. Conventional methods have fallen short of providing adequate 3D forc…
LQR-CBF-RRT*: Safe and Optimal Motion Planning
Guang Yang, Mingyu Cai, Ahmad Ahmad +3
We present LQR-CBF-RRT*, an incremental sampling-based algorithm for offline motion planning. Our framework leverages the strength of Control Barrier Functions (CBFs) and Linear Qu…