Félix de la Paz López

Reactive navigation in real environments using partial center of area method

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.

Consistent robot localization using Polar Scan Matching based on Kalman Segmentation

This work presents a revision of polar scan-matching procedure (PSM) in order to obtain an accurate robot localization in long runs without applying any other later procedure. In order to obtain an accurate robot pose estimation in long runs, PSM uses some SLAM procedure to correct error introduced by the scan-matching procedure. PSM compares scan points obtained from different positions, we have observed that if it associates points belonging to different objects, significant errors could appear in pose estimation. In our approach, an advanced line segmentation algorithm, based on Kalman filtering, is used to prevent as much as possible this kind of associations and to improve other areas in the original procedure. This new scan-matching procedure is named Polar Scan Matching based on Kalman Segmentation (PSM-KS). Experimental results in simulations show a reasonably accurate robot pose estimation, that outperform the accuracy obtained using odometry only, with low execution times. Consistent maps are obtained by simply overlapping estimated segments drawn from estimated poses. Consistent robot localization using only scan matching.Consistent robot mapping using only scan matching.Laser scan segmentation by means of regression using Kalman filtering.

Natural and Artificial Computation in Engineering and Medical Applications

The Vehicle Routing Problem with Time Windows relates to frequently occuring real world problems in logistics. Much work has been done on solving static routing problems but solving the dynamic variants has not been given an equal amount of attention, while these are even more relevant to most companies in logistics and transportation. In this work an Ant Colony Optimization algorithm for solving the Dynamic Vehicle Routing Problem with Time Windows is proposed. Customers and time windows are inserted during the working day and need to be integrated in partially committed solutions. Results are presented on a benchmark that generalizes Solomon’s classical benchmark with varying degrees of dynamicity and different variants, including pheromone preservation and the min-max ant system.

Natural and Artificial Models in Computation and Biology

Natural And Artificial Models In Computation And Biology Are you looking for ebook natural and artificial models in computation and biology? You will be glad to know that right now natural and artificial models in computation and biology is available on our online library. With our online resources, you can find natural and artificial models in computation and biology easily without hassle, since there are more than millions titles available in our ebook databases.

Improving area center robot navigation using a novel range scan segmentation method

When using raw 2D range measures to delimit the border for the free area sensed by a robot, the noise makes the sensor to yield a cloud of points, which is an imprecise border. This vagueness pose some problems for robot navigation using area center methods, due to free area split points locations. The basic method, when locating split points, does not take into account environmental features, only the raw cloud of points. In order to determine accurately such environmental features we use a novel range scan segmentation method. This method has the interesting characteristic of being adaptive to environment noise, in the sense that we do not need to fix noise standard deviation, even different areas of the same scan can have different deviations, e. g. a wall besides a hedge. Procedure execution time is in the order of milliseconds for modern processors. Information about interesting navigational features is used to improve area center navigation by means of determining safer split points and developing the idea of dynamic split point. A dynamic split point change its position to a new feature if this new feature is considered more dangerous than the one marked by the split point.

Discretized ISO-learning neural network for obstacle avoidance in reactive robot controllers

Isotropic sequence order learning (ISO-learning) and its variations, input correlation only learning (ICO-learning) and ISO three-factor learning (ISO3-learning) are unsupervised neural algorithms to learn temporal differences. As robotic software operates mainly in discrete time domain, a discretization of ISO-learning is needed to apply classical conditioning to reactive robot controllers. Discretization of ISO-learning is achieved by modifications to original rules: weights sign restriction, to adequate ISO-learning devices outputs to the usually predefined kinds of connections (excitatory/inhibitory) used in neural networks, and decay term in learning rate for weights stabilization. Discrete ISO-learning devices are included into neural networks used to learn simple obstacle avoidance in the reactive control of two real robots.

Topological Maps for Robot's Navigation: A Conceptual Approach

In this paper we present an example of incremental build up of a topological map to be used by a mobile robot which is programmed for navigation tasks. For this purpose we will use the concept of virtual expansion of the receptive field and invariant properties of the centre of areas in a region of open space around the robot. Then we propose, as basic elements in the buildingof this map, polygons of open space detected around the robot and referred to centres of area. The data structure that underlies our map is a graph where each node contains an open space polygon and where each arc represents the connectivity between these polygons.

Bioinspired Computation in Artificial Systems

ing Classification Models Heterogeneity to Build Clinical Group Diagnosis Support Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Oscar Marin-Alonso, Daniel Ruiz-Fernández, and Antonio Soriano-Paya Using EEG Signals to Detect the Intention of Walking Initiation and Stop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 Enrique Hortal, Andrés Úbeda, Eduardo Iáñez, Eduardo Fernández, and Jose M. Azoŕın Low-cost Remote Monitoring of Biomedical Signals . . . . . . . . . . . . . . . . . . . 288 J.M. Morales, C. Dı́az-Piedra, L.L. Di Stasi, Pablo Mart́ınez-Cañada, and S. Romero Asynchronous EEG/ERP Acquisition for EEG Teleservices . . . . . . . . . . . . 296 M.A. Lopez-Gordo, Pablo Padilla, F. Pelayo Valle, and Eduardo Fernandez XXII

Artificial Computation in Biology and Medicine

ing Classification Models Heterogeneity to Build Clinical Group Diagnosis Support Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Oscar Marin-Alonso, Daniel Ruiz-Fernández, and Antonio Soriano-Paya Using EEG Signals to Detect the Intention of Walking Initiation and Stop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 Enrique Hortal, Andrés Úbeda, Eduardo Iáñez, Eduardo Fernández, and Jose M. Azoŕın Low-cost Remote Monitoring of Biomedical Signals . . . . . . . . . . . . . . . . . . . 288 J.M. Morales, C. Dı́az-Piedra, L.L. Di Stasi, Pablo Mart́ınez-Cañada, and S. Romero Asynchronous EEG/ERP Acquisition for EEG Teleservices . . . . . . . . . . . . 296 M.A. Lopez-Gordo, Pablo Padilla, F. Pelayo Valle, and Eduardo Fernandez XVI

Improved Polar Scan-Matching Using an Advanced Line Segmentation Algorithm

This work presents an enhanced polar scan-matching procedure (E-PSM) that obtains its inputs from the application of an advanced line segmentation algorithm to the laser range returns. Additionally, a set of alternative methods based on local and global optimization algorithms is introduced. Results from robot simulation tests are provided for different ranges of laser range return noise and odometry sensor error levels. The results show that the proposed E-PSM algorithm and one of the methods based on global optimization yield good robot pose estimation precision while keeping computational costs at a reasonable level.