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

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.Postprint (author’s final draft

Map format for mobile robot map-based autonomous navigation

This technical report defines the spatial representation and the map file format used in a mobile robot map-based autonomous navigation system designed to be deployed in urban areas. After a discussion about common requirements of spatial representations for map-based mobile robot autonomous navigation, a proposed environment model that fulfills previously discussed requirements is formally presented. An example of a map representing an outdoor area of an university campus of about 10000m2 is given to better illustrate the map format. Finally, the report shows simulation results on global localization and path planning using the proposed map

Guiding and regrouping people missions in urban areas using cooperative multi-robot task allocation

Peer ReviewedPostprint (author’s final draft

Optimizing operating rules of multiple source water supply systems in terms of system reliability and resulting operating costs

This Presentation is brought to you for free and open access by the City College of New York at CUNY Academic Works. It has been accepted forinclusion in International Conference on Hydroinformatics by an authorized administrator of CUNY Academic Works. For more information, pleasecontact [email protected] and operation of a multiple-objective multisource water supply system from the point of view of the conjunctive use of water sources is a very complex problem whose solution is not just obtained using analytical models but also through a negotiation process among stakeholders and in which Public Bodies have a main role. For these reasons, this problem has been addressed using conservative approaches based on simulation models or simulation–linear optimization models parameterized using few parameters which, in general, are already covered by existing generalized modelling tools using a longer or shorter trial and error process. However, these conservative approaches have drawbacks and constraints when dealing with certain complexities of water supply systems (i.e.: non-linearity, uncertainty or stochastic nature) that may prevent them of finding an optimal solution. This paper identifies and tests suitable simulation-optimization approaches found in existing generalized modeling tools for optimizing operating rules of multisource water supply systems in terms of system guarantee and resulting operating costs. The main purpose is to find out whether these approaches are already covering the decision support needs of managers, Public Bodies or other stakeholders involved in the operation of these systems, or ‘ad-hoc’ tools may be needed.Peer ReviewedPostprint (published version

Autoencoders for Semi-Supervised Water Level Modeling in Sewer Pipes with Sparse Labeled Data

More frequent and thorough inspection of sewer pipes has the potential to save billions in utilities. However, the amount and quality of inspection are impeded by an imprecise and highly subjective manual process. It involves technicians judging stretches of sewer based on video from remote-controlled robots. Determining the state of sewer pipes based on these videos entails a great deal of ambiguity. Furthermore, the frequency with which the different defects occur differs a lot, leading to highly imbalanced datasets. Such datasets represent a poor basis for automating the labeling process using supervised learning. With this paper we explore the potential of self-supervision as a method for reducing the need for large numbers of well-balanced labels. First, our models learn to represent the data distribution using more than a million unlabeled images, then a small number of labeled examples are used to learn a mapping from the learned representations to a relevant target variable, in this case, water level. We choose a convolutional Autoencoder, a Variational Autoencoder and a Vector-Quantised Variational Autoencoder as the basis for our experiments. The best representations are shown to be learned by the classic Autoencoder with the Multi-Layer Perceptron achieving a Mean Absolute Error of 9.93. This is an improvement of 9.62 over the fully supervised baseline.Peer ReviewedPostprint (published version

Leakage detection and localization method based on a hybrid inverse/direct modelling approach suitable for handling multiple-leak scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. Nonetheless, the assumption of single-leak scenarios is usually considered and may not hold in real applications. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios in a large class of water distribution networks. This method can be seen as an upgrade of a direct-modeling approach in which a global search method based on Genetic Algorithms (GAs) has been integrated in order to estimate the water loss hotspots and their size. This is an inverse / direct modelling method which seeks to take benefit from both approaches: the exploration capability of GAs and the straightforwardness and reliability offered by the availability of an accurate hydraulic model. The application of the resulting method in a district metered area of the Barcelona water distribution network is provided and discussed.Peer ReviewedPostprint (author's final draft

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

Drinking water utilities in urban areas are facing new challenges in their real-time operation: limited water resources, intensive energy requirements, a growing population, a costly and ageing infrastructure, increasingly stringent regulations, and increased attention towards the environmental impact of water use. The efficient use of resources is becoming a priority for water managers and the recent advances in ICT technologies can provide solutions to this end. Real-time management in water networks may be considered as a process comprising two different levels: (i) Monitoring, which is concerned with the observation and estimation of the current state of a system and the detection/diagnosis of abnormal situations. It is achieved through sensors and communications technology, together with mathematical models; and (ii) Control, related to computing and applying the best admissible control strategies for network actuators. Optimal control seeks to optimize a given set of operational goals related to the network performance, such as efficiency in resource use, environmental impact, etc. Real-time monitoring and control techniques can significantly improve the use of water and energy resources in water networks. This paper addresses the developments of the European project EFFINET, which proposes a novel integrated water resource management system based on advanced ICT technologies of automation and telecommunications for improving the efficiency of drinking water networks in terms of water use, energy consumption, water loss minimization, and water quality guarantees by addressing the real-time monitoring and control levels.Peer ReviewedPostprint (author’s final draft

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

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

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

A three-dof actuated robot

This article presents the realization of a tensegrity-based robot composed of a three-bar symmetric prismlike minimal tensegrity configuration. Statics and kinematics are studied presenting the workspace for the designed robot. After a detailed implementation description of the physical robot, some trajectories within its workspace are analyzed. Although our long-term objective is to provide mobile tensegrity-based robots to the community, this work studies a case in which the robot is anchored to the ground. This provides us with a first insight of how these structures should be actuated and sensed to produce movement.Postprint (author’s final draft