TOPO

Topological navigation of mobile robots

Main researcher: M.A. Salichs

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Description

To build AD architecture, the equipment took as a model the way
human mental processes work. The developed architecture has two
levels: a Deliberative level and an Automatic one. In the Deliberative
level we find the skills that
require high computational time as a consequence of high level
reasoning. In the Automatic level lay the skills that interact with
robot sensors and actuators. In the AD architecture there are
several sequencers working in a concurrent way.

The navigation system was called AURON. Its autonomy is based on the interaction of four main components: the autonomy generation of an environment representation, the planning of a sequence of actions and perceptions which guide the robot from an initial event to a final event based on an optimization approach, the navigation that converts sequences in real movements and supervises all the process, and the last one, the relocalization that allows to place the robot again in the representation of the environment if it is lost. All these components have been implemented in the AD control architecture as deliberative skills.

Entries:
Visual Approach Skill for a Mobile Robot using Learning and Fusion of Simple Skills
Robotics and Autonomous Systems. num. 3 , vol. 38 , pages: 157 – 170 , 2002
R. Barber M.A. Salichs
Navigation of Mobile Robots: Open Questions
Robotica. num. 3 , vol. 18 , pages: 227 – 234 , 2000
L. Moreno M.A. Salichs
Visual Approach Skill for a Mobile Robot using Learning and Fusion of Simple Skills
Robotics and Autonomous Systems. num. 3 , vol. 38 , pages: 157 – 170 , 2002
R. Barber M.A. Salichs
Navigation of Mobile Robots: Open Questions
Robotica. num. 3 , vol. 18 , pages: 227 – 234 , 2000
L. Moreno M.A. Salichs
Visual Approach Skill for a Mobile Robot using Learning and Fusion of Simple Skills
Robotics and Autonomous Systems. num. 3 , vol. 38 , pages: 157 – 170 , 2002
R. Barber M.A. Salichs

Entries:
Voronoi Diagram and Fast Marching applied to Path Planning
2006 IEEE International conference on Robotics and Automation. ICRA 2006, 2006, Orlando,Florida, USA
S. Garrido D. Blanco L. Moreno
Autonomous Monitoring And Reaction To Failures In A Topological Navigation System
2nd International Conference on Informatics in Control, Automation and Robotics, 2005, Barcelona, Spain
V. Egido R. Barber M.A. Salichs
A Door Lintel Locator Sensor for Mobile Robot Topological Navigation
IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2005, Sofia, Bulgaria
V. Egido R. Barber M.A. Salichs
A Framework For Complex Skill Generation
The 5th IFAC Symposium on Intelligent Autonomous Vehicles. Lisboa, 2004, Lisboa, Portugal
M. Rivero R. Barber M.A. Salichs
A Planner For Topological Navigation Based On Previous Experiences
The 5th IFAC Symposium on Intelligent Autonomous Vehicles, 2004, Lisboa, Portugal
V. Egido R. Barber M.A. Salichs

Entries:
Machine Learning and Robot Perception
chapter: Continuous Reinforcement Learning Algorithm for Skills Learning in an Autonomous Mobile Robot pages: 137 – 165. Springer , ISBN: 978-3-540-26549, 2005
V. Egido R. Barber M.A. Salichs
Machine Learning and Robot Perception
chapter: Continuous Reinforcement Learning Algorithm for Skills Learning in an Autonomous Mobile Robot pages: 137 – 165. Springer , ISBN: 978-3-540-26549, 2005
V. Egido R. Barber M.A. Salichs
Machine Learning and Robot Perception
chapter: Continuous Reinforcement Learning Algorithm for Skills Learning in an Autonomous Mobile Robot pages: 137 – 165. Springer , ISBN: 978-3-540-26549, 2005
V. Egido R. Barber M.A. Salichs
Machine Learning and Robot Perception
chapter: Continuous Reinforcement Learning Algorithm for Skills Learning in an Autonomous Mobile Robot pages: 137 – 165. Springer , ISBN: 978-3-540-26549, 2005
V. Egido R. Barber M.A. Salichs
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