Robotic control systems based on bioinspired multi-agent systems: application of the principles of neuroscience to robotics

Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.

Inclusion of immersive virtual learning environments and visual control systems to support the learning of students with Asperger syndrome

This paper presents the use of immersive virtual reality systems in the educational intervention with Asperger students. The starting points of this study are features of these students' cognitive style that requires an explicit teaching style supported by visual aids and highly structured environments. The proposed immersive virtual reality system, not only to assess the student's behavior and progress, but also is able to adapt itself to the student's specific needs. Additionally, the immersive reality system is equipped with sensors that can determine certain behaviors of the students. This paper determines the possible inclusion of immersive virtual reality as a support tool and learning strategy in these particular students' intervention. With this objective two task protocols have been defined with which the behavior and interaction situations performed by participant students are recorded. The conclusions from this study talks in favor of the inclusion of these virtual immersive environments as a support tool in the educational intervention of Asperger syndrome students as their social competences and executive functions have improved.

System for robot control inspired by the functionality and organisation of the human nervous system

This paper presents a model of a control system for robot systems inspired by the functionality and organisation of human neuroregulatory system. Our model was specified using software agents within a formal framework and implemented through Web Services. This approach allows the implementation of the control logic of a robot system with relative ease, in an incremental way, using the addition of new control centres to the system as its behaviour is observed or needs to be detailed with greater precision, without the need to modify existing functionality. The tests performed verify that the proposed model has the general characteristics of biological systems together with the desirable features of software, such as robustness, flexibility, reuse and decoupling.

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.

Contextual visual localization: cascaded submap classification, optimized saliency detection, and fast view matching

In this paper, we present a novel coarse-to-fine visual localization approach: contextual visual localization. This approach relies on three elements: (i) a minimal-complexity classifier for performing fast coarse localization (submap classification); (ii) an optimized saliency detector which exploits the visual statistics of the submap; and (iii) a fast view-matching algorithm which filters initial matchings with a structural criterion. The latter algorithm yields fine localization. Our experiments show that these elements have been successfully integrated for solving the global localization problem. Context, that is, the awareness of being in a particular submap, is defined by a supervised classifier tuned for a minimal set of features. Visual context is exploited both for tuning (optimizing) the saliency detection process, and to select potential matching views in the visual database, close enough to the query view.

3D plane-based egomotion for SLAM on semi-structured environment

Several works deal with 3D data in SLAM problem. Data come from a 3D laser sweeping unit or a stereo camera, both providing a huge amount of data. In this paper, we detail an efficient method to extract planar patches from 3D raw data. Then, we use these patches in an ICP-like method in order to address the SLAM problem. Using ICP with planes is not a trivial task. It needs some adaptation from the original ICP. Some promising results are shown for outdoor environment.

Practical experiences on a real pumping system emulated by a hardware model and used as a remote laboratory

Paper submitted to ACE 2013, 10th IFAC Symposium on Advances in Control Education, University of Sheffield, UK, August 28-30, 2013.

Mathematical modelling of the lower urinary tract

The lower urinary tract is one of the most complex biological systems of the human body as it involved hydrodynamic properties of urine and muscle. Moreover, its complexity is increased to be managed by voluntary and involuntary neural systems. In this paper, a mathematical model of the lower urinary tract it is proposed as a preliminary study to better understand its functioning. Furthermore, another goal of that mathematical model proposal is to provide a basis for developing artificial control systems. Lower urinary tract is comprised of two interacting systems: the mechanical system and the neural regulator. The latter has the function of controlling the mechanical system to perform the voiding process. The results of the tests reproduce experimental data with high degree of accuracy. Also, these results indicate that simulations not only with healthy patients but also of patients with dysfunctions with neurological etiology present urodynamic curves very similar to those obtained in clinical studies.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.