Zachary Taylor

About

Zachary Taylor is a leading researcher in robotics, specializing in autonomous navigation, 3D mapping, and trajectory optimization for aerial and ground robots. His most influential work, "Continuous-time trajectory optimization for online UAV replanning," has garnered over 378 combined citations, introducing a real-time collision avoidance method that enables multirotor UAVs to operate safely in partially unknown, unstructured environments—a critical advancement for field robotics. Taylor has also pioneered the use of Signed Distance Fields (SDFs) as a natural representation for both mapping and planning, with his work on voxblox and C-blox providing scalable, consistent dense mapping frameworks that bridge the gap between 3D reconstruction and robotic planning. His research extends to agricultural robotics, where he developed multi-spectral feature learning for orchard fruit segmentation, and to collaborative multi-robot systems, improving localization between aerial and ground platforms through elevation maps. With over 750 total citations across his publications, Taylor’s contributions have fundamentally shaped how robots perceive, map, and navigate complex 3D environments, making his work essential reading for anyone advancing autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Continuous-time trajectory optimization for online UAV replanning

   247 citations · 2016
2. 2
   Continuous-time trajectory optimization for online UAV replanning

   131 citations · 2016
3. 3
   Orchard fruit segmentation using multi-spectral feature learning

   97 citations · 2013
4. 4
   Signed Distance Fields: A Natural Representation for Both Mapping and Planning

   74 citations · 2016
5. 5
   Sparse 3D Topological Graphs for Micro-Aerial Vehicle Planning

   70 citations · 2018
6. 6
   C-blox: A Scalable and Consistent TSDF-based Dense Mapping Approach

   60 citations · 2018
7. 7
   Collaborative localization of aerial and ground robots through elevation maps

   29 citations · 2016
8. 8
   Collaborative Localization of Aerial and Ground Robots through Elevation Maps

   20 citations · 2016
9. 9
   Voxblox: Building 3D Signed Distance Fields for Planning

   18 citations · 2016
10. 10
    Sparse 3D Topological Graphs for Micro-Aerial Vehicle Planning

    5 citations · 2018

Key Collaborators

Contact & Links