A comprehensive dynamic model for class-1 tensegrity systems based on quaternions

a b s t r a c t In this paper we propose a new dynamic model, based on quaternions, for tensegrity systems of class-1. Quaternions are used to represent orientations of a rigid body in the 3-dimensional space eliminating the problem of singularities. Moreover, the equations based on quaternions allow to perform more precise calculations and simulations because they do not use trigonometric functions for the representation of angles. We present a thorough introduction of tensegrities and the current state of research. We also introduce the quaternions and provide in the appendix some important details and useful properties. Applying the Euler-Lagrange approach we derive a comprehensive dynamic model, first for a simple rigid bar in the space and, at last, for a class-1 tensegrity system. We present two model forms: a matrix and a vectorial form. The first more compact and easier to write, the latter more suitable to apply the tools and the theory based on vector fields

On The Structure Of The Objective Function For A Pressure Sensor Placement Optimizing Methodology Based On Genetic Algorithms Applied To Model-Based Leakage Localization In Distribution Water Networks

Real-time monitoring of distribution water networks relies on the deployment of sensors and the availability of their measurements in order to predict the system state and assess its performance. A meaningful application of this methodology is the detection and localization of leaks using model-based approaches. Since the number of sensors is limited because of budget constraints, it is important to place these devices in locations where the effectiveness of the leakage diagnosis is maximized. Finding the best sensor distribution is a global optimization problem defined by an objective function that might depend on different factors. Therefore, deriving the correct structure of such function is a crucial step as a wrong definition would lead towards a confusing optimal solution affecting negatively the monitoring performance. In general, sensor placement optimization methods describe objective functions using factors related to the amount of undistinguishable leaks. More concretely, the methods first compute groups of locations where leaks cannot be differentiated and then maximize this number of groups or minimize their size. In this paper, additional factors are presented to accurately represent the requirements of the leak diagnosis phase. These include other statistical figures related to the size of groups, geographical characteristics like the group’s extension area, levels of sensitivity that indicate whether a location is more or less sensible to pressure changes, etc. The objective of this study is to review several factors in order to comprehend their behaviour and justify or discard them for the objective function. The indicators under study are evaluated by means of a cross-correlation analysis applied to the scenario defined by the District Metered Area of the Barcelona water distribution. Results indicate the existence of different independency levels between the indicators that allow us to select those with less redundancy

Real-time software for mobile robot simulation and experimentation in cooperative environments

Trabajo presentado al 1st SIMPAR celebrado en Venecia del 3 al 6 de noviembre de 2008.This paper presents the software being developed at IRI (Institut de Robotica i Informatica Industrial) for mobile robot autonomous navigation in the context of the European project URUS (Ubiquitous Robots in Urban Settings). In order that a deployed sensor network and robots operating in the environment cooperate in terms of information sharing, main requirements are real-time performance and the integration of information coming from remote machines not onboard the robot. Moreover, the project involves a group of eleven industrial and academic partners, therefore software integration issues are critical. The proposed software framework is based on the YARP middleware and has been tested in real and simulated experiments.This work was supported by projects: 'Ubiquitous networking robotics in urban settings' (E-00938), 'CONSOLIDER-INGENIO 2010 Multimodal interaction in pattern recognition and computer vision' (V-00069), 'Robotica ubicua para entornos urbanos' (J-01225). Partially supported by Consolider Ingenio 2010, project CSD2007-00018, CICYT project DPI2007-61452, and IST-045062 of the European Community Union.Peer Reviewe

A decision support system for on-line leakage localization

This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integrates a model-based leakage localization methodology based on the use of on-line telemetry information, as well as a water network calibrated hydraulic model. The application of the resulting decision support software tool in a district metered area (DMA) of the Barcelona distribution network is provided and discussed. The obtained results show that the leakage detection and localization may be performed efficiently reducing the required time. © 2014 Elsevier Ltd.The authors wish to thank the support received by the AM0901 project funded by R+i Alliance (Suez Environnement) and by the EFFINET grant FP7-ICT-2012-318556 of the European Commission.Peer Reviewe

Real-time monitoring and control for efficient management of drinking water networks: Barcelona case study

Trabajo presentado a la 11th International Conference on Hydroinformatics celebrada en New York (US) del 17 al 21 de agosto de 2014.This research has been partially funded by the DGR of Generalitat de Catalunya (SAC group Ref. 2009/SGR/1491), Doctorat Industrial AGAUR-2013-DI-041 and by EFFINET: Efficient Integrated Real-time Monitoring and Control of Drinking Water Networks (FP7-ICT2011-8-318556).Peer Reviewe

Research at the learning and vision mobile robotics group 2004-2005

Spanish Congress on Informatics (CEDI), 2005, Granada (España)This article presents the current trends on wheeled mobile robotics being pursued at the Learning and Vision Mobile Robotics Group (IRI). It includes an overview of recent results produced in our group in a wide range of areas, including robot localization, color invariance, segmentation, tracking, audio processing and object learning and recognition.This work was supported by projects: 'Supervised learning of industrial scenes by means of an active vision equipped mobile robot.' (J-00063), 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).Peer Reviewe

Onto computing the uncertainty for the odometry pose estimate of a mobile robot

Prsentado al 12th ETFA celebrado del 25 al 28 de septiembre de 2007 en Patras (Grecia).Solving the navigation issue for a mobile robot in a 2D space requires using internal and external sensors, so researchers try to fuse data from different sensors using methods as for example Kalman filtering. Those methods need an estimation of the uncertainty in the pose estimates obtained from the sensory system, usually expressed by a covariance matrix and obtained from experimental data. In a previous work, a general method to obtain the uncertainty in the odometry pose estimate was proposed. Here, with the aim of assessing the generality of the method, the general formulation is particularized for a given differential driven robot. Its kinematic model relates two internal measurements: the instantaneous displacement of both, right and left wheels. The obtained formulation is validated experimentally and compared against Kalman filtering.Peer Reviewe

Qualitative modelling of complex systems by means of fuzzy inductive reasoning. Variable selection and search space reduction.

Fuzzy Inductive Reasoning (FIR) is a modelling and simulation methodology capable of generating a qualitative input-output model of a system from real-valued trajectories of its physical variables. The functioning basis of FIR is to qualitatively learn the behaviour of a system from its past real data. This is an interesting feature when dealing with ill-defined, usually large-scale systems, for which an accurate description is not available but only data trajectories of the process.FIR finds in a (huge) search space model the so-called optimal mask that indicates which variables best explain any given output. Unfortunately, any algorithm that can find the optimal mask is necessarily of exponential complexity, i.e., the number of masks to be visited grows exponentially with the number of available input variables. This makes the FIR methodology, in its actual implementation, impractical for those cases in which it would be most useful, i.e., large-scale systems.The thesis discusses whether sub-optimal search algorithms or methods of pre-simplifying a large-scale system are most suitable for dealing effectively and efficiently with the problem of deriving qualitative FIR models for them. The mask search space of FIR must be reduced in order to compute a model of a large-scale system in an affordable amount of time. To this aim, basically two lines of thought are given in the present dissertation. The first one is to directly simplify the candidate mask that is proposed to FIR. This can be done either directly, by reducing the number of input variables to the FIR model, or indirectly, using sub-optimal mask search algorithms. Two new sub-optimal mask search algorithms are proposed. The first method is another variant of a hill-climbing technique, which results in a high-quality mask while still converging in polynomial time. The second method is a new variant of a statistical approach that is based on spectral coherence functions.The second line of research in this dissertation is to obtain a decomposition of the system into subsystems. This would allow obtaining a model of the system from its subsystems, which in turn reduces the computational time needed for the overall effort. Given a k-variable system, the cost of computing a unique k-variable model is much higher than computing a set of p models of jp With these complementary lines of work, two complete methodologies can be proposed, each of which enables the construction of qualitative models of complex systems. The former, based in simplifying the number of potential inputs to the FIR models, is an energy-based method, capable of detecting the variables at given delays that are more closely related to the considered output of the system. The latter proposes a decomposition of the overall system into subsystems. With the research presented in this thesis, the FIR modelling capabilities have been extended with capabilities for modelling large-scale systems within a reasonable time

A 2D unknown contour recovery method immune to system non-linear effects

IEEE International Conference on Robotics and Biomimetics (ROBIO), 2006, Kunming (China)A method to recover general 2D a priori unknown contours using a kind of special optic sensor is described. Contour recovery is an important task for exploratory operations in unknown environments as well as for more practical applications such as grinding or deburring. It is not an easy task since the recovered contour (generally obtained using encoder data) is severely distorted due to errors in the kinematic model of the robot and to the non-linearities of its actuators. Some mathematical models have been presented to partially compensate for those effects, but they require a deep knowledge of both the robot and sensor models which are difficult to obtain accurately, and normally imply an adaptive non-linear control to estimate some of the unknown parameters of the model. Our approach, in despite of its simplicity, is intrinsically immune to non-linearities, which allows us to eliminate most of the distortions added to the sensor data. A simple algorithm to follow unknown planar contours is presented and used to test the performance of this approach in comparison to the one using encoder data. Experimental results and practical problems are also discussed.This work was supported by the project 'Estació de treball multibraç' (I-00544).Peer Reviewe