Topological Maps for Robot's Navigation: A Conceptual Approach
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
The centre of area method as a basic mechanism for representation and navigation
Robotics and Autonomous Systems
Partial Center of Area Method Used for Reactive Autonomous Robot Navigation
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Mathematical Foundations of the Center of Area Method for Robot Navigation
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Improving area center robot navigation using a novel range scan segmentation method
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes
Engineering Applications of Artificial Intelligence
Journal of Intelligent and Robotic Systems
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Using inspiration from our perception on how humans select the path to walk in crowded areas, a new method for reactive autonomous robot navigation is proposed. The method uses only a part of the detected free space in front of the robot to compute a partial center of area. It can guide the robot safely for robust wandering while the center of area remains accessible. In some cases it is necessary to split and shrink the detected area used for navigation to overcome a transitional inaccessible center of area. The method was slightly modified so that the robot can reach a stimulus goal while avoiding obstacles. Method implementation and modifications are explained in detail. Some experiments were carried to test the method with a real robot in mid-complex environments. In previous works the method was extensively tested in simulations and the good results obtained there are confirmed by the real robot tests.