Home ›
Entities
› academia
› Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration
Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration
Research article (Journal of Terramechanics, 2021) · cited 22× · AI/ML
Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration
Summary
Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration is a scholarly article[1].
Key Facts
Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration. Retrieved May 24, 2026, from https://4ort.xyz/entity/machine-learning-in-planetary-rovers-a-survey-of-learning-versus-classical-estimation-methods-in-terramechanics-for-in-s
MLA“Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/machine-learning-in-planetary-rovers-a-survey-of-learning-versus-classical-estimation-methods-in-terramechanics-for-in-s.
BibTeX@misc{4ortxyz_machine-learning-in-planetary-rovers-a-survey-of-learning-versus-classical-estimation-methods-in-terramechanics-for-in-s_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration}}, year = {2026}, url = {https://4ort.xyz/entity/machine-learning-in-planetary-rovers-a-survey-of-learning-versus-classical-estimation-methods-in-terramechanics-for-in-s}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Machine learning in planetary rovers: A survey of learning versus classical estimation methods in terramechanics for in situ exploration — https://4ort.xyz/entity/machine-learning-in-planetary-rovers-a-survey-of-learning-versus-classical-estimation-methods-in-terramechanics-for-in-s (retrieved 2026-05-24)
