Research Article
Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter
Table 4
RFNN weights of trajectory 2.
| | | | | | | |
| 0.101 | 0.882 | 2.538 | 3.730 | 4.181 | 4.344 | 4.363 | 0.756 | 6.545 | 18.82 | 27.66 | 31.01 | 32.22 | 32.36 | 0.866 | 7.494 | 21.55 | 31.67 | 35.50 | 36.89 | 37.05 | 0.996 | 8.624 | 24.80 | 36.45 | 40.86 | 42.45 | 42.64 | 0.098 | 0.852 | 2.451 | 3.601 | 4.037 | 4.195 | 4.213 | 0.172 | 1.493 | 4.295 | 6.312 | 7.075 | 7.351 | 7.383 | 0.484 | 4.192 | 12.05 | 17.72 | 19.86 | 20.64 | 20.73 | 0.937 | 8.110 | 23.32 | 34.28 | 38.42 | 39.92 | 40.10 | 0.509 | 4.409 | 12.68 | 18.63 | 20.89 | 21.70 | 21.80 | | | | | | | | 0.466 | 4.036 | 11.61 | 17.06 | 19.12 | 19.87 | 19.95 |
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