Mathematical Problems in Engineering / 2017 / Article / Tab 2

Research Article

A New Terrain Classification Framework Using Proprioceptive Sensors for Mobile Robots

Table 2

Comparison of the proposed terrain classification framework with traditional method on benchmark feature vectors. MMFCC and FFT are adopted as benchmark feature vectors for acoustics and acceleration data sources, respectively. The driving speed is 2 m/s. The number in brackets is the dimensionality of the optimal feature subset corresponding to the best result.

Data sourceFeature vectorSVMRFkNNNB

MMFCC (18D)89.6%87.1%80.8%77.9%
FFT (200D)90.4%89.17%75.42%84.6%
FFT (200D)94.2%92.92%72.08%88.3%
FFT (200D)92.1%92.95%91.3%88.2%
FFT (200D)93.3%92.92%91.3%90.8%

Proposed framework97.9% (80D)99.6% (90D)95% (50D)97.5% (100D)

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.