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A Learning-based Approach to Motion Planning with State Lattices in Off-Road Environments

Year: 2025

Type: conference-paper

Source: 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)

DOI: 10.1109/case58245.2025.11163734

Authors: Joshua Rosser, Garrett Warnell, Eli Lancaster, Felix Sanchez, Ethan Fahnestock, Eric Damm, Jason Gregory, Thomas M. Howard

Institutions: University of Rochester, The University of Texas at Austin, DEVCOM Army Research Laboratory, United States Army Combat Capabilities Development Command, Booz Allen Hamilton (United States), Massachusetts Institute of Technology

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: Advanced Research Projects Agency

OpenAlex ID: W4414432155

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Cites: 25

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