The NATURE autonomy stack: an open-source stack for off-road navigation

Christopher Goodin; Marc N. Moore; Daniel W. Carruth; Christopher R. Hudson; Lucas D. Cagle; Stefan Wapnick; Paramsothy Jayakumar

doi:10.1117/12.3010131

7 June 2024 The NATURE autonomy stack: an open-source stack for off-road navigation

Christopher Goodin, Marc N. Moore, Daniel W. Carruth, Christopher R. Hudson, Lucas D. Cagle, Stefan Wapnick, Paramsothy Jayakumar

Author Affiliations +

Proceedings Volume 13055, Unmanned Systems Technology XXVI; 1305503 (2024) https://doi.org/10.1117/12.3010131
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Off-road autonomous navigation remains an ongoing challenge for autonomous ground vehicles (AGV). The challenges of navigating in an unstructured environment include identifying and detecting both positive and negative obstacles, distinguishing navigable from non-navigable vegetation, identifying soft soil, and negotiating rough or sloping terrain. While many recent works have dealt with various aspects of the off-road navigation problem, up to now there has not been a free and open-source autonomy stack for off-road that included integrated modules for perception, planning, and control. Therefore, we have recently developed the NATURE (Navigating All Terrains Using Robotic Exploration) autonomy stack as a publicly available resource to facilitate the advancement of off-road navigation research. The NATURE stack is implemented using the Robotic Operating System (ROS) and can be built to work with both ROS-1 and ROS-2. The modular nature of the NATURE stack makes it an ideal resource for researchers who want to evaluate a particular algorithm for perception, planning, or control without developing an entire navigation stack from scratch. NATURE features several options for both global and local path planning including A*, artificial potential field, and spline-based planning, as well as multiple options for perception including a simple geometrically based obstacle finder and more advanced custom traversability algorithm derived from 3D lidar. In this presentation we give an overview of the NATURE stack and show some past uses of the stack in both simulated and field experiments.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Christopher Goodin, Marc N. Moore, Daniel W. Carruth, Christopher R. Hudson, Lucas D. Cagle, Stefan Wapnick, and Paramsothy Jayakumar "The NATURE autonomy stack: an open-source stack for off-road navigation", Proc. SPIE 13055, Unmanned Systems Technology XXVI, 1305503 (7 June 2024); https://doi.org/10.1117/12.3010131

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