Name
Abstract | ||
|---|---|---|
This paper implements an automated transportation system allowing passengers on a car-like robot to reach their destination safely, intelligently and autonomously. Different components of the system are described such as localization based on Hector SLAM, humans detection based on HOG (Histograms of Oriented Gradient) descriptor and intelligent navigation based on FNN (Fuzzy neural networks) approach. To show the whole system effectiveness for the car-like mobile robot Robucar, experimentations were done in ROS, in an unknown human environment. |
Year | Venue | Keywords |
|---|---|---|
2016 | 2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) | Mobile robots, autonomous systems, intelligent, navigation, automated transport, humans detection, Hector SLAM, obstacles avoidance, neural networks, fuzzy logic, target seeking, HOG descriptor, Ada-Boost learning |
Field | DocType | Citations |
Computer vision,Histogram,Simulation,Fuzzy neural,Robot kinematics,Artificial intelligence,Engineering,Mobile robot navigation,Artificial neural network,Simultaneous localization and mapping,Robot,Mobile robot | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Somia Brahimi | 1 | 0 | 0.34 |
| Rachid Tiar | 2 | 1 | 1.72 |
| Ouahiba Azouaoui | 3 | 36 | 7.12 |
| m lakrouf | 4 | 4 | 1.14 |
| Malik Loudini | 5 | 8 | 3.64 |