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| Author(s): |
Jefferson Rodrigo de Souza
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2014-03-21 |
| Examining board members: |
Denis Fernando Wolf;
Heloisa de Arruda Camargo;
Valdir Grassi Junior;
Josue Junior Guimarães Ramos;
João Luis Garcia Rosa
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| Advisor: | Denis Fernando Wolf |
| Abstract | |
Autonomous navigation is a fundamental problem in the field of mobile robotics. Algorithms capable of driving a robot to its destination safely and efficiently are a prerequisite for mobile robots to successfully perform different tasks that may be assigned to them. Depending on the complexity of the environment and the task to be executed, programming of navigation algorithms is not a trivial problem. This thesis approaches the development of autonomous navigation systems based on supervised learning techniques. More specifically, two distinct problems have been addressed: a robot/vehicle navigation in urban environments and robot navigation in unstructured environments. In the first case, the robot/vehicle must avoid obstacles and keep itself in the road based on examples provided by a human driver. In the second case, the robot should identify and avoid unstructured areas (higher vibration), reducing energy consumption. In this case, learning was based on information obtained by sensors. In either case, supervised learning algorithms have been capable of allowing the robots to navigate in a safe and efficient manner during the experimental tests (AU) | |
| FAPESP's process: | 09/11614-4 - Autonomous Navigation Using Supervised Learning |
| Grantee: | Jefferson Rodrigo de Souza |
| Support Opportunities: | Scholarships in Brazil - Doctorate |