José Ramón Álvarez-Sánchez

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.

Partial Center of Area Method Used for Reactive Autonomous Robot Navigation

A new method for reactive autonomous robot navigation using the center of area of detected free space around the robot is described. The proposed method uses only part of detected free space in front of the robot to compute a partial center of area. It is then used to guide the robot in a path suitable for smooth and robust wandering in complex environments. A simple modification in the algorithm can make it useful for obstacle avoidance in reaching a stimulus goal. The proposed method is used in some examples of simulated experiments on map navigation and wandering and it is compared with standard wandering using Aria library from MobileRobots. Also some experiments in obstacle avoidance navigation to reach a stimulus goal are shown in different maps.

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.

A biological neuroprocessor for robotic guidance using a center of area method

This paper introduces a neuroinformatic system using human neuroblastoma cultures and centre of area learning for basic robotic guidance. Multielectrode Arrays Setups have been designed for direct culturing neural cells over silicon or glass substrates, providing the capability to stimulate and record simultaneously populations of neural cells. The main objective of this work will be to control a robot using this biological neuroprocessor and a simple centre of area learning scheme. The final system could be applied for testing how chemicals affect the behaviour of the robot or to establish the basis for new hybrid optogenetic learning.

A client-server architecture for remotely controlling a robot using a closed-loop system with a biological neuroprocessor

This paper introduces an open-source real-time system that remotely controls a robot using human neuroblastoma cultures and a client-server architecture. Multielectrode array set-ups have been designed for direct culturing of neural cells over silicon or glass substrates, providing the capability simultaneously to stimulate and record populations of neural cells. However, it is very difficult to attach these neural cells to the robot structure due to the special conditions of the biological material. The main objective of this research is to build a client-server system for remotely connecting a robot to a neural culture in a closed-loop experimentation. The robot sensors will feed the biological neuroprocessor, while the neural activity will be used for guiding the robot, controlling in this way the robotic behaviour.

A hybrid robotic control system using neuroblastoma cultures

The main objective of this work is to analyze the computing capabilities of human neuroblastoma cultured cells and to define connection schemes for controlling a robot behavior Multielectrode Array (MEA) setups have been designed for direct culturing neural cells over silicon or glass substrates, providing the capability to stimulate and record simultaneously populations of neural cells This paper describes the process of growing human neuroblastoma cells over MEA substrates and tries to modulate the natural physiologic responses of these cells by tetanic stimulation of the culture We show that the large neuroblastoma networks developed in cultured MEAs are capable of learning: establishing numerous and dynamic connections, with modifiability induced by external stimuli and we propose an hybrid system for controlling a robot to avoid obstacles.

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