AirSim Drone Racing Lab. - Ratnesh Madaan; Nicholas Gyde; Sai Vemprala; Matthew Brown; Keiko Nagami; Tim Taubner; Eric Cristofalo; Davide Scaramuzza 001; Mac Schwager; Ashish Kapoor (NeurIPS (Competition and Demos), 2019)

HJB-RL: Initializing Reinforcement Learning with Optimal Control Policies Applied to Autonomous Drone Racing. - Keiko Nagami; Mac Schwager (Robotics: Science and Systems, 2021)

Aerial Grasping and the Velocity Sufficiency Region. - Tony G. Chen; Kenneth A. W. Hoffmann; Jun En Low; Keiko Nagami; David Lentink; Mark R. Cutkosky (IEEE Robotics Autom. Lett., 2022)

NerfBridge: Bringing Real-time, Online Neural Radiance Field Training to Robotics. - Javier Yu; Jun En Low; Keiko Nagami; Mac Schwager (CoRR, 2023)

State Estimation and Belief Space Planning Under Epistemic Uncertainty for Learning-Based Perception Systems. - Keiko Nagami; Mac Schwager (IEEE Robotics Autom. Lett., 2024)

Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps. - Timothy Chen; Ola Shorinwa; Joseph Bruno; Aiden Swann; Javier Yu; Weijia Zeng; Keiko Nagami; Philip M. Dames; Mac Schwager (IEEE Trans. Robotics, 2025)

SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuum. - Jun En Low; Maximilian Adang; Javier Yu; Keiko Nagami; Mac Schwager (IEEE Robotics Autom. Lett., 2025)

VISTA: Open-Vocabulary, Task-Relevant Robot Exploration with Online Semantic Gaussian Splatting. - Keiko Nagami; Timothy Chen; Javier Yu; Ola Shorinwa; Maximilian Adang; Carlyn Dougherty; Eric Cristofalo; Mac Schwager (CoRR, 2025)