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| Content Provider | Springer Nature Link |
|---|---|
| Author | Silva, Catarina Ribeiro, Bernardete |
| Copyright Year | 2003 |
| Abstract | Neural architectures have been proposed to navigate mobile robots within several environment definitions. In this paper a new neural modular constructive approach to navigate mobile robots in unknown environments is presented. The problem, in its basic form, consists of defining and executing a trajectory to a pre-defined goal while avoiding all obstacles, in an unknown environment. Some crucial issues arise when trying to solve this problem, such as an overflow of sensorial information and conflicting objectives. Most neural network (NN) approaches to this problem focus on a monolithic system, i.e., a system with only one neural network that receives and analyses all available information, resulting in conflicting training patterns, long training times and poor generalisation. The work presented in this article circumvents these problems by the use of a constructive modular NN. Navigation capabilities were proven with the NOMAD 200 mobile robot. |
| Starting Page | 200 |
| Ending Page | 211 |
| Page Count | 12 |
| File Format | |
| ISSN | 09410643 |
| Journal | Neural Computing and Applications |
| Volume Number | 12 |
| Issue Number | 3-4 |
| e-ISSN | 14333058 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2003-11-14 |
| Publisher Place | London |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Constructive algorithms Mobile robot navigation Modular neural networks Sensor fusion |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Software |
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