From the 1 of 4 linked papers with an AI index.
4 papers
Flatness-Preserving Residual Learning for Real-Time Tight Quadrotor Formation Flight
Pei-An Hsieh, Fengjun Yang, Nikolai Matni +1
The paper introduces a physics‑informed residual dynamics learning method that keeps a multi‑quadrotor system differentially flat, enabling a fast feedback‑linearization controller…
Neural Navigation Functions for Zero-Shot Generalizable Motion Planning
Benjamin D. Shaffer, Pei-An Hsieh, Brooks Kinch +2
We introduce Neural Navigation Functions (Neural-NF), a learned reactive navigation function capable of zero-shot transfer across unseen environment geometries. Neural-NF places da…
Online Adaptation for Flying Quadrotors in Tight Formations
Pei-An Hsieh, Kong Yao Chee, M. Ani Hsieh
The task of flying in tight formations is challenging for teams of quadrotors because the complex aerodynamic wake interactions can destabilize individual team members as well as t…
Flying Quadrotors in Tight Formations using Learning-based Model Predictive Control
Kong Yao Chee, Pei-An Hsieh, George J. Pappas +1
Flying quadrotors in tight formations is a challenging problem. It is known that in the near-field airflow of a quadrotor, the aerodynamic effects induced by the propellers are com…