Research Article
Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter
Table 3
RFNN weights of trajectory 1.
| | | | | | | |
| 0.701 | 5.396 | 15.40 | 20.60 | 23.32 | 24.49 | 24.82 | 0.209 | 1.616 | 4.614 | 6.174 | 6.986 | 7.337 | 7.437 | 0.533 | 4.110 | 11.73 | 15.69 | 17.76 | 18.65 | 18.90 | 0.359 | 2.772 | 7.913 | 10.58 | 11.98 | 12.58 | 12.75 | 0.713 | 5.493 | 15.67 | 20.97 | 23.73 | 24.93 | 25.26 | 0.007 | 0.053 | 0.152 | 0.204 | 0.230 | 0.242 | 0.245 | 0.639 | 4.926 | 14.06 | 18.81 | 21.28 | 22.35 | 22.66 | 0.126 | 0.972 | 2.775 | 3.713 | 4.202 | 4.413 | 4.473 | 0.774 | 5.965 | 17.02 | 22.78 | 25.78 | 27.07 | 27.44 | 0.537 | 4.138 | 11.81 | 15.80 | 17.88 | 18.78 | 19.03 | | | | | | | | 0.220 | 1.910 | 5.496 | 8.076 | 9.053 | 9.406 | 9.448 |
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