Specific parameters of the test sequence in the a multi-modal and multi-scenario dataset for ground robots dataset.

Specific parameters of the test sequence in the a multi-modal and multi-scenario dataset for ground robots dataset.

<p>Specific parameters of the test sequence in the a multi-modal and multi-scenario dataset for ground robots dataset.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Hongliang Zou (20707270) (author)
مؤلفون آخرون: Chen Zhou (466781) (author), Haibo Li (629817) (author), Xueyan Wang (141449) (author), Yinmei Wang (20707273) (author)
منشور في: 2025
الموضوعات:
Neuroscience
Evolutionary Biology
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
tightly coupled lidar
proposed method improved
3d point cloud
urban navigation dataset
square error recorded
smallest average error
decreased localization accuracy
real robot dog
overall localization accuracy
inertial data fusion
localization error
inertial data
sensor localization
rotational error
robot dogs
autonomous navigation
xlink ">
theoretical path
study proposes
significantly lower
significantly increasing
highest root
gps environments
five sequences
experiments conducted
complex environments
competing approaches
algorithms evaluated
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الوصف
الملخص:<p>Specific parameters of the test sequence in the a multi-modal and multi-scenario dataset for ground robots dataset.</p>

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