Table 5 MAE and variance of static estimation on real data
From: LiDAR DNN based self-attitude estimation with learning landscape regularities
MAE [deg] {Var. [\(\mathrm {deg^2}\)]} | Dataset# | ||||
|---|---|---|---|---|---|
3 | 4 | 5 | 6 | ||
Before fine-tuning | LiDAR DNN (ours) | 11.68 {108.84} | 13.71 {105.20} | 11.29 {77.18} | 24.31 {157.94} |
---"--- | Camera DNN | 6.67 {25.92} | 6.42 {22.90} | 8.72 {83.84} | 14.95 {38.24} |
After fine-tuning | LiDAR DNN (ours) | 4.08 {6.88} | 5.27 {8.65} | 5.72 {11.80} | 16.60 {61.97} |
---"--- | Camera DNN | 4.82 {18.13} | 4.83 {16.03} | 5.83 {55.13} | 14.28 {33.51} |
Statistics | 23.61 {96.13} | 22.28 {98.97} | 27.33 {86.82} | 15.91 {85.83} | |