Lunar Payload Logistics: Advancing Autonomous Control for Lunar Surface Transporter Vehicles
Abstract
An autonomous forklift rover, the Artemis Navigating Transporter System (ANTS), was modeled and validated in NVIDIA Isaac Sim with ROS 2 Nav2 to demonstrate reliable payload pickup, transport, and delivery across uneven lunar terrain. We integrate D* Lite global planning into Nav2, combined with DWA local obstacle avoidance and behavior-tree control, to handle uneven terrain, dense obstacles, and partially unknown environments. Three simulation scenarios, flat terrain, obstacle-dense fields, and high-fidelity lunar landscapes, demonstrated path efficiencies above 87%, robust forklift alignment, and stable operation under realistic hardware constraints. These results benchmark single-rover autonomy for lunar surface transporter vehicles and establish a foundation for future cooperative multi-rover logistics in support of NASA’s Artemis infrastructure.
Fields of Study & Subjects
Robotic Path Planning Algorithms
Reinforcement Learning in Robotics
Robotics and Sensor-Based Localization
Publication details
- Journal / source
- AIAA SciTech Forum
- Publication date
- 8 January 2026