Shane Windsor — accepted AI-conference papers

2025

Tendon-driven Grasper Design for Aerial Robot Perching on Tree Branches

Haichuan Li, Ziang Zhao, Ziniu Wu, Parth Potdar, Long Tran, Ali Tahir Karasahin +3

IROS 2025

Protecting and restoring forest ecosystems has become an important conservation issue. Although various robots have been used for field data collection to protect forest ecosystems, the complex terrain and dense canopy make the data collection less efficient. To address this challenge, an aerial pla

Cited by 2 Source ↗code ↗Scholar ↗

2022

Sim-to-Real Transfer for Fixed-Wing Uncrewed Aerial Vehicle: Pitch Control by High-Fidelity Modelling and Domain Randomization

Daichi Wada, Sergio Araujo-Estrada, Shane Windsor

RA-L 2022

Deep reinforcement learning has great potential to automatically generate flight controllers for uncrewed aerial vehicles (UAVs), however these controllers often fail to perform as expected in real world environments due to differences between the simulation environment and reality. This letter expe

Cited by 9 Source ↗Scholar ↗