Results of the quadratic position estimation (ATE RMSE [cm]) for each model in the replica dataset. Our method minimizes the error in the quadratic position estimation without significant bias.

Results of the quadratic position estimation (ATE RMSE [cm]) for each model in the replica dataset. Our method minimizes the error in the quadratic position estimation without significant bias.

<p>Results of the quadratic position estimation (ATE RMSE [cm]) for each model in the replica dataset. Our method minimizes the error in the quadratic position estimation without significant bias.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Zhanrong Li (5103872) (author)
مؤلفون آخرون:	Jiajie Han (21432828) (author), Chao Jiang (122046) (author), Haosheng Su (21432831) (author)
منشور في:	2025
الموضوعات:	Ecology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> currently three different types supports dynamic scaling trajectory error accuracy achieves stable reconstruction recently proposed kolmogorov complex outdoor environments kan network based based implicit representation region sampling nerf complex environments random sampling map representation fidelity reconstruction error returns arnold network slam based based slam based approach vit loss traditional slam slam system significantly improves rapidly developing optimization process large scenes indoor datasets gaussian functions exposure compensation existing nerf dense coverage datasets show approach replaces approach reduces
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