DSpace Collection:
http://hdl.handle.net/2117/2253
20140724T23:12:59Z

Chanceconstrained model predictive control for drinking water networks
http://hdl.handle.net/2117/23369
Title: Chanceconstrained model predictive control for drinking water networks
Authors: Grosso Pérez, Juan Manuel; OcampoMartínez, Carlos; Puig Cayuela, Vicenç; Joseph Duran, Bernat
Abstract: This paper addresses a chanceconstrained model predictive control (CCMPC) strategy for the management of drinking water networks (DWNs) based on a finite horizon stochastic optimisation problem with joint probabilistic (chance) constraints. In this approach, water demands are considered additive stochastic disturbances with nonstationary uncertainty description, unbounded support and known (or approximated) quasiconcave probabilistic distribution. A deterministic equivalent of the stochastic problem is formulated using Boole's inequality to decompose joint chance constraints into single chance constraints and by considering a uniform allocation of risk to bound these later constraints. The resultant deterministicequivalent optimisation problem is suitable to be solved with tractable quadratic programming (QP) or second order cone programming (SOCP) algorithms. The reformulation allows to explicitly and easily propagate uncertainty over the prediction horizon, and leads to a costefficient management of risk that consists in a dynamic backoff to avoid frequent violation of constraints. Results of applying the proposed approach to a real case study  the Barcelona DWN (Spain)  have shown that the network performance (in terms of operational costs) and the necessary backoff (to cope with stochastic disturbances) are optimised simultaneously within a single problem, keeping tractability of the solution, even in largescale networks. The general formulation of the approach and the automatic computation of proper backoff within the MPC framework replace the need of experiencebased heuristics or bilevel optimisation schemes that might compromise the tradeoff between profits, reliability and computational burden. © 2014 Elsevier Ltd.
20140701T11:48:48Z

Exhaustive linearization for robust camera pose and focal length estimation
http://hdl.handle.net/2117/22931
Title: Exhaustive linearization for robust camera pose and focal length estimation
Authors: Peñate Sanchez, Adrián; AndradeCetto, Juan; MorenoNoguer, Francesc
Abstract: We propose a novel approach for the estimation of the pose and focal length of a camera from a set of 3Dto2D point correspondences. Our method compares favorably to competing approaches in that it is both more accurate than existing closed form solutions, as well as faster and also more accurate than iterative ones. Our approach is inspired on the EPnP algorithm, a recent O(n) solution for the calibrated case. Yet we show that considering the focal length as an additional unknown renders the linearization and relinearization techniques of the original approach no longer valid, especially with large amounts of noise. We present new methodologies to circumvent this limitation termed exhaustive linearization and exhaustive relinearization which perform a systematic exploration of the solution space in closed form. The method is evaluated on both real and synthetic data, and our results show that besides producing precise focal length estimation, the retrieved camera pose is almost as accurate as the one computed using the EPnP, which assumes a calibrated camera.
20140508T17:15:25Z

Robotized plant probing: leaf segmentation utilizing timeofflight data
http://hdl.handle.net/2117/22930
Title: Robotized plant probing: leaf segmentation utilizing timeofflight data
Authors: Alenyà Ribas, Guillem; Dellen, Babette; Foix Salmerón, Sergi; Torras, Carme
Abstract: Supervision of longlasting extensive botanic
experiments is a promising robotic application that some recent technological advances have made feasible. Plant modeling for this application has strong demands, particularly in what concerns threedimensional (3D) information gathering and speed.
20140508T16:53:20Z

Efficient asymptoticallyoptimal path planning on manifolds
http://hdl.handle.net/2117/22927
Title: Efficient asymptoticallyoptimal path planning on manifolds
Authors: Jaillet, Leonard Georges; Porta Pleite, Josep Maria
Abstract: This paper presents an efficient approach for asymptoticallyoptimal path planning on implicitlydefined configuration spaces. Recently, several asymptoticallyoptimal path planners have been introduced, but they typically exhibit slow convergence rates. Moreover, these planners can not operate on the configuration spaces that appear in the presence of kinematic or contact constraints, such as when manipulating an object with two arms or with a multifingered hand. In these cases, the configuration space usually becomes an implicit manifold embedded in a higherdimensional joint ambient space. Existing samplingbased path planners on manifolds focus on finding a feasible solution, but they do not optimize the quality of the path in any sense and, thus, the returned solution is usually not adequate for direct execution. In this paper, we adapt several techniques to accelerate the convergence of the asymptoticallyoptimal planners and we use higherdimensional continuation tools to deal with the case of implicitlydefined configuration spaces. The performance of the proposed approach is evaluated through various experiments.
20140508T16:04:11Z

Planning reliable paths with Pose SLAM
http://hdl.handle.net/2117/22926
Title: Planning reliable paths with Pose SLAM
Authors: Valencia Carreño, Rafael; Morta Garriga, Martí; AndradeCetto, Juan; Porta Pleite, Josep Maria
Abstract: The maps that are built by standard featurebased simultaneous localization and mapping (SLAM) methods cannot be directly used to compute paths for navigation, unless enriched with obstacle or traversability information, with the consequent increase in complexity. Here, we propose a method that directly uses the Pose SLAM graph of constraints to determine the path between two robot configurations with lowest accumulated pose uncertainty, i.e., the most reliable path to the goal. The method shows improved navigation results when compared with standard pathplanning strategies over both datasets and realworld experiments.
20140508T15:57:06Z

Local stimulus disambiguation with global motion filters predicts adaptive surround modulation
http://hdl.handle.net/2117/22740
Title: Local stimulus disambiguation with global motion filters predicts adaptive surround modulation
Authors: Dellen, Babette; Torras, Carme
Abstract: Humans have no problem segmenting different motion stimuli despite the ambiguity of local motion signals. Adaptive surround modulation, i.e., the apparent switching between integrative and antagonistic modes, is assumed to play a crucial role in this process. However, so far motion processing models based on local integration have not been able to provide a unifying explanation for this phenomenon. This motivated us to investigate the problem of local stimulus disambiguation in an alternative and fundamentally distinct motionprocessing model which uses global motion filters for velocity computation. Local information is reconstructed at the end of the processing stream through the constructive interference of global signals, i.e., inverse transformations. We show that in this model local stimulus disambiguation can be achieved by means of a novel filter embedded in this architecture. This gives rise to both integrative and antagonistic effects which are in agreement with those observed in psychophysical experiments with humans, providing a functional explanation for effects of motion repulsion
20140428T17:45:33Z

Turing's algorithmic lens: from computability to complexity theory
http://hdl.handle.net/2117/22738
Title: Turing's algorithmic lens: from computability to complexity theory
Authors: Díaz Cort, Josep; Torras, Carme
Abstract: The decidability question, i.e., whether any mathematical statement could be computationally proven true or false, was raised by Hilbert and remained open until Turing answered it in the negative. Then, most efforts in theoretical computer science turned to complexity theory and the need to classify decidable problems according to their difficulty. Among others, the classes P (problems solvable in polynomial time) and NP (problems solvable in nondeterministic polynomial time) were defined, and one of the most challenging scientific quests of our days arose: whether P = NP. This still open question has implications not only in computer science, mathematics and physics, but also in biology, sociology and economics, and it can be seen as a direct consequence of Turing’s way of looking through the algorithmic lens at different disciplines to discover how pervasive computation is.
20140428T17:13:15Z

Operational predictive optimal control of Barcelona water transport network
http://hdl.handle.net/2117/22536
Title: Operational predictive optimal control of Barcelona water transport network
Authors: Pascual Pañach, Josep; Romera Formiguera, Juli; Puig Cayuela, Vicenç; Cembrano Gennari, Gabriela; Creus Rodriguez, Ramon; Minoves Ruiz, Meritxell
Abstract: This paper describes the application of modelbased predictive control (MPC) techniques to the supervisory flow management in largescale drinking water networks including a telemetry/telecontrol system. MPC is used to generate flow control strategies (setpoints for the regulatory controllers) from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, safety storage volumes in the network and smoothness of the flow control actions. The designed management strategies are applied to a model of a real case study: the drinking water transport network of Barcelona (Spain)
20140407T12:25:32Z

Path planning under kinematic constraints by rapidly exploring manifolds
http://hdl.handle.net/2117/22501
Title: Path planning under kinematic constraints by rapidly exploring manifolds
Authors: Jaillet, Leonard Georges; Porta Pleite, Josep Maria
Abstract: The situation arising in path planning under kinematic constraints, where the valid configurations define a manifold embedded in the joint ambient space, can be seen as a limit case of the wellknown narrow corridor problem. With kinematic constraints, the probability of obtaining a valid configuration by sampling in the joint ambient space is not low but null, which complicates the direct application of samplingbased path planners. This paper presents the AtlasRRT algorithm, which is a planner especially tailored for such constrained systems that builds on recently developed tools for higherdimensional continuation. These tools provide procedures to define charts that locally parametrize a manifold and to coordinate the charts, forming an atlas that fully covers it. AtlasRRT simultaneously builds an atlas and a bidirectional rapidly exploring random tree (RRT), using the atlas to sample configurations and to grow the branches of the RRTs, and the RRTs to devise directions of expansion for the atlas. The efficiency of AtlasRRT is evaluated in several benchmarks involving highdimensional manifolds embedded in large ambient spaces. The results show that the combined use of the atlas and the RRTs produces a more rapid exploration of the configuration space manifolds than existing approaches.
20140402T17:59:56Z

Gainscheduled Smith predictor PIDbased LPV controller for openflow canal control
http://hdl.handle.net/2117/22354
Title: Gainscheduled Smith predictor PIDbased LPV controller for openflow canal control
Authors: Bolea Monte, Yolanda; Puig Cayuela, Vicenç; Blesa Izquierdo, Joaquim
Abstract: In this paper, a gainscheduled Smith Predictor PID controller is proposed for the control of an open flow canal system that allows to deal with large variation in operating conditions. A linear parameter varying (LPV) control oriented model for openflow channel systems based on a Second Order Delay Hayami (SODH) model is proposed. Exploiting the second order structure of this model, an LPV PID controller is designed using and linear matrix inequalities (LMI) pole placement. The controller structure includes a Smith Predictor, real time estimated parameters from measurements (including the known part of the delay) that schedule the controller and predictor and unstructured dynamic uncertainty which covers the unknown portion of the delay. Finally, the proposed controller is validated in a case study based on a single real reach canal: the Lunax Gallery at Gascogne (France).
20140324T12:51:25Z

A robot learning from demonstration framework to perform forcebased manipulation tasks
http://hdl.handle.net/2117/22275
Title: A robot learning from demonstration framework to perform forcebased manipulation tasks
Authors: Rozo Castañeda, Leonel; Jiménez Schlegl, Pablo; Torras, Carme
Abstract: This paper proposes an endtoend learning from demonstration framework for teaching forcebased manipulation tasks to robots. The strengths of this work are manyfold. First, we deal with the problem of learning through force perceptions exclusively. Second, we propose to exploit haptic feedback both as a means for improving teacher demonstrations and as a human–robot interaction tool, establishing a bidirectional communication channel between the teacher and the robot, in contrast to the works using kinesthetic teaching. Third, we address the wellknown what to imitate? problem from a different point of view, based on the mutual information between perceptions and actions. Lastly, the teacher’s demonstrations are encoded using a Hidden Markov Model, and the robot execution phase is developed by implementing a modified version of Gaussian Mixture Regression that uses implicit temporal information from the probabilistic model, needed when tackling tasks with ambiguous perceptions. Experimental results show that the robot is able to learn and reproduce two different manipulation tasks, with a performance comparable to the teacher’s one.
20140318T17:51:39Z

Linear parameter varying modeling and identification for realtime control of openflow irrigation canals
http://hdl.handle.net/2117/21378
Title: Linear parameter varying modeling and identification for realtime control of openflow irrigation canals
Authors: Bolea Monte, Yolanda; Puig Cayuela, Vicenç; Blesa Izquierdo, Joaquim
Abstract: Irrigation canals are openflow water hydraulic systems, whose objective is mainly to convey water from its source down to its final users. They are large distributed systems characterized by nonlinearity and
dynamic behavior that depends on the operating point. Moreover, in canals with multiple reaches dynamic behavior is highly affected by the coupling among them. The physical model for those systems leads to a distributedparameter model whose description usually requires partial differential equations (PDEs). However, the solution and parameter estimation of those PDE equations can only be obtained numerically and imply quite timeconsuming computations that make them not suitable for realtime control purposes. Alternatively, in this paper, it will be shown that openflow canal systems can be suitably represented for control purposes by using linear parametervarying (LPV) models. The advantage of this approach compared to the use of PDE equation is that allows simpler models which are suitable for control design and whose parameters can be easily identified from inputeoutput data by means of classical identification techniques. In this paper, the wellknown controloriented, model named integral delay zero (IDZ), that is able to represent the canal dynamics around a given operating point by means of a linear timeinvariant (LTI) model is extended to multiple operating points by means of an LPV model. The derivation of this LPV model for singlereach openflow canal systems as well as its extension to multiplereach openflow canals is proposed. In particular, the proposed methodology allows deriving the model structure and estimating model parameters using data by means of identification techniques. Thus, a graybox control model is obtained whose validation is carried out using singlepool and twopool test canals obtaining satisfactory results.
20140127T12:25:40Z

Adaptive threshold generation in robust fault detection using interval models: Timedomain and frequencydomain approaches
http://hdl.handle.net/2117/21245
Title: Adaptive threshold generation in robust fault detection using interval models: Timedomain and frequencydomain approaches
Authors: Puig Cayuela, Vicenç; Montes de Oca Armeaga, Saul; Blesa Izquierdo, Joaquim
Abstract: In this paper, robust fault detection is addressed on the basis of evaluating the residual energy that it is compared against worstcase value (threshold) generated considering parametric modeling uncertainty
using interval models. The evaluation of the residual/threshold energy can be performed either in the time or frequency domain. This paper proposes methods to compute such energy in the two domains. The first method generates the adaptive threshold in the time domain through determining the worstcase time evolution of the residual energy using a zonotopebased algorithm. The second method evaluates the worstcase energy evolution in the frequency domain using the Kharitonov polynomials. Results obtained using both approaches are related through the Parseval’s theorem. Finally, two application examples (a smart servoactuator and a two DOFs helicopter) will be used to assess the validity of the proposed approaches and compare the results obtained.
20140115T12:15:53Z

Experimental study of hydrogen purge effects on performance and efficiency of an opencathode proton exchange membrane fuel cell system
http://hdl.handle.net/2117/20645
Title: Experimental study of hydrogen purge effects on performance and efficiency of an opencathode proton exchange membrane fuel cell system
Authors: Strahl, Stephan; Husar, Attila Peter; Riera Colomer, Jordi
Abstract: The performance and efficiency of an opencathode PEM fuel cell system in deadended anode (DEA) configuration and hydrogen purges is analyzed in this work. Excess water and crossedover nitrogen in the
anode decrease the hydrogen concentration at the catalyst surface, which in turn causes performance losses.
Purging the anode with hydrogen removes water and nitrogen and thus recovers the performance. However, this means wasting hydrogen and decreasing overall system efficiency. Gas chromatography was used to detect and quantify the accumulated nitrogen in the anode during DEA operation. The experiments show that the major performance limitation in the studied system is related to water instead of nitrogen. Moreover, oxygen was detected in the anode exhaust gas after long purge intervals, which is an indicator for corrosion of the cathode
carbon support structure. Experimental observations revealed that the need for a hydrogen purge strongly depends on the operating conditions and the stateofhealth of the fuel cell. It is shown that flooding on the anode and drying of the cathode catalyst layer may occur simultaneously during purged operation. Therefore, purge
decisions must be evaluated online, depending on the operating conditions.
20131118T14:36:01Z

Planning singularityfree paths on closedchain manipulators
http://hdl.handle.net/2117/20248
Title: Planning singularityfree paths on closedchain manipulators
Authors: Bohigas Nadal, Oriol; Henderson, Michael E.; Ros Giralt, Lluís; Manubens Ferriol, Montserrat; Porta Pleite, Josep Maria
Abstract: This paper provides an algorithm for computing singularityfree paths on closedchain manipulators. Given two
nonsingular configurations of the manipulator, the method attempts to connect them through a path that maintains a
minimum clearance with respect to the singularity locus at all points, which guarantees the controllability of the manipulator everywhere along the path. The method can be applied to nonredundant manipulators of general architecture, and it is resolutioncomplete. It always returns a path whenever one exists at a given resolution, or determines path nonexistence
otherwise. The strategy relies on defining a smooth manifold that maintains a onetoone correspondence with the singularityfree
Cspace of the manipulator, and on using a higherdimensional continuation technique to explore this manifold systematically from one configuration, until the second configuration is found.
If desired, the method can also be used to compute an exhaustive atlas of the whole singularityfree component reachable from a
given configuration, which is useful to rapidly resolve subsequent planning queries within such component, or to visualize the
singularityfree workspace of any of the manipulator coordinates.
Examples are included that demonstrate the performance of the method on illustrative situations.
20131001T13:29:52Z