INVESTIGACIÓN

@article{doi:10.1108/IR-09-2014-0395,

title = {Acquisition of welding skills in industrial robots},

author = {Aviles-Vi\~{n}as, Jaime F and Lopez-Juarez, Ismael and Rios-Cabrera, Reyes },

url = {http://dx.doi.org/10.1108/IR-09-2014-0395},

doi = {10.1108/IR-09-2014-0395},

year  = {2015},

date = {2015-01-01},

journal = {Industrial Robot: An International Journal},

volume = {42},

number = {2},

pages = {156-166},

abstract = {Purpose \textendash The purpose of this paper was to propose a method based on an Artificial Neural Network and a real-time vision algorithm, to learn welding skills in industrial robotics. Design/methodology/approach \textendash By using an optic camera to measure the bead geometry (width and height), the authors propose a real-time computer vision algorithm to extract training patterns and to enable an industrial robot to acquire and learn autonomously the welding skill. To test the approach, an industrial KUKA robot and a welding gas metal arc welding machine were used in a manufacturing cell. Findings \textendash Several data analyses are described, showing empirically that industrial robots can acquire the skill even if the specific welding parameters are unknown. Research limitations/implications \textendash The approach considers only stringer beads. Weave bead and bead penetration are not considered. Practical implications \textendash With the proposed approach, it is possible to learn specific welding parameters despite of the material, type of robot or welding machine. This is due to the fact that the feedback system produces automatic measurements that are labelled prior to the learning process. Originality/value \textendash The main contribution is that the complex learning process is reduced into an input-process-output system, where the process part is learnt automatically without human supervision, by registering the patterns with an automatically calibrated vision system.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Navarro-Gonzalez2015,

title = {On-line incremental learning for unknown conditions during assembly operations with industrial robots},

author = {Navarro-Gonzalez, Jose Luis and Lopez-Juarez, Ismael and Ordaz-Hernandez, Keny and Rios-Cabrera, Reyes },

url = {http://dx.doi.org/10.1007/s12530-014-9125-x},

doi = {10.1007/s12530-014-9125-x},

issn = {1868-6486},

year  = {2015},

date = {2015-01-01},

journal = {Evolving Systems},

volume = {6},

number = {2},

pages = {101--114},

abstract = {The assembly operation using industrial robots can be accomplished successfully in well-structured environments where the mating pair location is known in advance. However, in real-world scenarios there are uncertainties associated to sensing, control and modelling errors that make the assembly task very complex. In addition, there are also unmodeled uncertainties that have to be taken into account for an effective control algorithm to succeed. Among these uncertainties, it can be mentioned disturbances, backlash and aging of mechanisms. In this paper, a method to overcome the effect of those uncertainties based on the Fuzzy ARTMAP artificial neural network (ANN) to successfully accomplish the assembly task is proposed. Experimental work is reported using an industrial 6 DOF robot arm in conjunction with a vision system for part location and wrist force/torque sensing data for assembly. Force data is fed into an ANN evolving controller during a typical peg in hole (PIH) assembly operation. The controller uses an incremental learning mechanism that is solely guided by the sensed forces. In this article, two approaches are presented in order to compare the incremental learning capability of the manipulator. The first approach uses a primitive knowledge base (PKB) containing 16 primitive movements to learn online the first insertion. During assembly, the manipulator learns new patterns according to the learning criteria which turn the PKB into an enhanced knowledge base (EKB). During a second insertion the controller uses effectively the EKB and operation improves. The second approach employs minimum information (it contains only the assembly direction) and the process starts from scratch. After several operations, that knowledge base increases by including only the needed patterns to perform the insertion. Experimental results showed that the evolving controller is able to assemble the matting pairs enhancing its knowledge whenever it is needed depending on the part geometry and level of expertise. Our approach is demonstrated through several PIH operations with different tolerances and part geometry. As the robot's expertise evolves, the PIH operation is carried out faster with shorter assembly trajectories.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{NavarroGonzalez201578b,

title = {On-line knowledge acquisition and enhancement in robotic assembly tasks},

author = {Navarro-Gonzalez, Jose Luis and Lopez-Juarez, Ismael and Rios-Cabrera, Reyes and Ordaz-Hernandez, Keny},

url = {http://www.sciencedirect.com/science/article/pii/S073658451400074X},

doi = {http://dx.doi.org/10.1016/j.rcim.2014.08.013},

issn = {0736-5845},

year  = {2015},

date = {2015-01-01},

journal = {Robotics and Computer-Integrated Manufacturing},

volume = {33},

pages = {78 - 89},

abstract = {Abstract Industrial robots are reliable machines for manufacturing tasks such as welding, panting, assembly, palletizing or kitting operations. They are traditionally programmed by an operator using a teach pendant in a point-to-point scheme with limited sensing capabilities such as industrial vision systems and force/torque sensing. The use of these sensing capabilities is associated to the particular robot controller, operative systems and programming language. Today, robots can react to environment changes specific to their task domain but are still unable to learn skills to effectively use their current knowledge. The need for such a skill in unstructured environments where knowledge can be acquired and enhanced is desirable so that robots can effectively interact in multimodal real-world scenarios. In this article we present a multimodal assembly controller (MAC) approach to embed and effectively enhance knowledge into industrial robots working in multimodal manufacturing scenarios such as assembly during kitting operations with varying shapes and tolerances. During learning, the robot uses its vision and force capabilities resembling a human operator carrying out the same operation. The approach consists of using a MAC based on the Fuzzy ARTMAP artificial neural network in conjunction with a knowledge base. The robot starts the operation having limited initial knowledge about what task it has to accomplish. During the operation, the robot learns the skill for recognising assembly parts and how to assemble them. The skill acquisition is evaluated by counting the steps to complete the assembly, length of the followed assembly path and compliant behaviour. The performance improves with time so that the robot becomes an expert demonstrated by the assembly of a kit with different part geometries. The kit is unknown by the robot at the beginning of the operation; therefore, the kit type, location and orientation are unknown as well as the parts to be assembled since they are randomly fed by a conveyor belt.},

note = {Special Issue on Knowledge Driven Robotics and Manufacturing},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Castelan2015,

title = {A Photometric Sampling Strategy for Reflectance Characterization and Transference},

author = {Castelan, Mario and Cruz-Perez, Elier and Torres-Mendez, Luz Abril},

url = {http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/1944},

year  = {2015},

date = {2015-01-01},

journal = {Computaci\'{o}n y Sistemas},

volume = {19},

number = {2},

pages = {255-272},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RAYGOSABARAHONA2015313,

title = {Control Libre de Modelo basado en Modos Deslizantes Integrales para Robots Submarinos Subactuados1},

author = {Raygoza-Barahona, Ruben and Olguin-Diaz, Ernesto and Parra-Vega, Vicente and Mu\~{n}oz-Ubando, L. A.},

url = {http://www.sciencedirect.com/science/article/pii/S1697791215000321},

doi = {http://dx.doi.org/10.1016/j.riai.2015.04.004},

issn = {1697-7912},

year  = {2015},

date = {2015-01-01},

journal = {Revista Iberoamericana de Automatica e Informatica Industrial RIAI},

volume = {12},

number = {3},

pages = {313 - 324},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SANCHEZFRAIRE2015154b,

title = {On the Brain Computer Robot Interface (BCRI) to Control Robots},

author = {Sanchez-Fraire, U. and Parra-Vega, Vicente and Martinez-Peon, D. and Sepulveda-Cervantes, G. and Sanchez-Orta, Anand and Mu\~{n}oz-Vazquez, Aldo Jonathan},

url = {http://www.sciencedirect.com/science/article/pii/S2405896315026506},

doi = {http://dx.doi.org/10.1016/j.ifacol.2015.12.026},

issn = {2405-8963},

year  = {2015},

date = {2015-01-01},

journal = {IFAC-PapersOnLine},

volume = {48},

number = {19},

pages = {154 - 159},

note = {11th IFAC Symposium on Robot Control SYROCO 2015},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{GARCIARODRIGUEZ2015220,

title = {Dexterous Dynamic Optimal Grasping of a Circular Object subject to Gravity with Soft-fingertips},

author = {Garci­a-Rodri­guez, R. and Villalva-Lucio, M. and Parra-Vega, Vicente},

url = {http://www.sciencedirect.com/science/article/pii/S2405896315026610},

doi = {http://dx.doi.org/10.1016/j.ifacol.2015.12.037},

issn = {2405-8963},

year  = {2015},

date = {2015-01-01},

journal = {IFAC-PapersOnLine},

volume = {48},

number = {19},

pages = {220 - 225},

note = {11th IFAC Symposium on Robot Control SYROCO 2015},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{MUNOZVAZQUEZ2015118,

title = {Control of Constrained Robot Manipulators based on Fractional Order Error Manifolds},

author = {Mu\~{n}oz-Vazquez, Aldo Jonathan and Parra-Vega, Vicente and Sanchez-Orta, Anand},

url = {http://www.sciencedirect.com/science/article/pii/S2405896315026440},

doi = {http://dx.doi.org/10.1016/j.ifacol.2015.12.020},

issn = {2405-8963},

year  = {2015},

date = {2015-01-01},

journal = {IFAC-PapersOnLine},

volume = {48},

number = {19},

pages = {118 - 123},

note = {11th IFAC Symposium on Robot Control SYROCO 2015},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{delosAngelesHernandez2015,

title = {A hybrid learning method composed by the orthogonal least-squares and the back-propagation learning algorithms for interval A2-C1 type-1 non-singleton type-2 TSK fuzzy logic systems},

author = {de los Angeles Hernandez, Maria and Melin, Patricia and Mendez, Gerardo M. and Castillo, Oscar and Lopez-Juarez, Ismael},

url = {http://dx.doi.org/10.1007/s00500-014-1287-8},

doi = {10.1007/s00500-014-1287-8},

issn = {1433-7479},

year  = {2015},

date = {2015-01-01},

journal = {Soft Computing},

volume = {19},

number = {3},

pages = {661--678},

abstract = {The purpose of this paper is to present a hybrid learning method for interval A2-C1 type-1 non-singleton type-2 TSK fuzzy logic system that uses the recursive orthogonal least-squares algorithm to tune the type-1 consequent parameters, and the back-propagation algorithm to tune the interval type-2 antecedent parameters. Based on the combination of these two training algorithms the new hybrid learning method changes the interval type-2 fuzzy model parameters adaptively and minimizes the proposed error function as the new type-1 non-singleton input--output data pairs are processed. Its antecedent sets are interval type-2 fuzzy sets, its consequent sets are type-1 fuzzy sets, and its inputs are type-1 non-singleton fuzzy numbers with uncertain standard deviations. Comparison with the non-hybrid interval A2-C1 type-1 non-singleton type-2 Takagi--Sugeno--Kang fuzzy logic system that only uses the back-propagation algorithm for both antecedent and consequent parameter's adaptation demonstrates that the proposed hybrid algorithm is a well-performing nonlinear adaptation that enables the interval type-2 fuzzy model to optimally match the nonlinear behavior of the process. The application of the interval type-2 fuzzy logic as adaptable predictor using the proposed hybrid learning method was constructed for the modeling and prediction of the transfer bar surface temperature in an industrial hot strip mill facility. Experimental results demonstrated that this method improves the temperature prediction performance of the interval A2-C1 type-1 non-singleton type-2 Takagi--Sugeno--Kang fuzzy logic system.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Treesatayapun:2015:DIA:2729770.2729786,

title = {Data Input-output Adaptive Controller Based on IF-THEN Rules for a Class of Non-affine Discrete-time Systems: The Robotic Plant},

author = {Treesatayapun, Chidentree},

url = {http://dx.doi.org/10.3233/IFS-141347},

doi = {10.3233/IFS-141347},

issn = {1064-1246},

year  = {2015},

date = {2015-01-01},

journal = {J. Intell. Fuzzy Syst.},

volume = {28},

number = {2},

pages = {661--668},

publisher = {IOS Press},

address = {Amsterdam, The Netherlands, The Netherlands},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Treesatayapun2015,

title = {A data-driven adaptive controller for a class of unknown nonlinear discrete-time systems with estimated PPD},

author = {Treesatayapun, Chidentree},

url = {http://www.sciencedirect.com/science/article/pii/S2215098615000051},

doi = {http://dx.doi.org/10.1016/j.jestch.2014.12.004},

issn = {2215-0986},

year  = {2015},

date = {2015-01-01},

journal = {Engineering Science and Technology, an International Journal},

volume = {18},

number = {2},

pages = {218 - 228},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{0964-1726-24-7-075008,

title = {Damage detection using the signal entropy of an ultrasonic sensor network},

author = {Rojas, Erick and Baltazar, Arturo and Loh, K.},

url = {http://stacks.iop.org/0964-1726/24/i=7/a=075008},

year  = {2015},

date = {2015-01-01},

journal = {Smart Materials and Structures},

volume = {24},

number = {7},

pages = {075008},

abstract = {Piezoelectric ultrasonic sensors used to propagate guided waves can potentially be implemented to inspect large areas in engineering structures. However, the inherent dispersion and noise of guided acoustic signals, multiple echoes in the structure, as well as a lack of an approximate or exact model, limit their use as a continuous structural health monitoring system. In this work, the implementation of a network of piezoelectric sensors randomly placed on a plate-like structure to detect and locate artificial damage is studied. A network of macro fiber composite (MFC) sensors working in a pitch\^{a}€“catch configuration was set on an aluminum thin plate 1.9 mm in thickness. Signals were analyzed in the time-scale domain using the discrete wavelet transform. The objectives of this work were threefold, namely to first develop a damage index based on the entropy distribution using short time wavelet entropy of the ultrasonic waves generated by a sensor network, second to determine the performance of an array of spare MFC sensors to detect artificial damage, and third to implement a time-of-arrival (TOA) algorithm on the gathered signals for damage location of an artificial circular discontinuity. Our preliminary test results show that the proposed methodology provides sufficient information for damage detection, which, once combined with the TOA algorithm, allows localization of the damage.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mu\~{n}oz-V\'{a}zquez2015,

title = {Continuous fractional sliding mode-like control for exact rejection of non-differentiable H\"{o}lder disturbances},

author = {Mu\~{n}oz-Vazquez, Aldo Jonathan and Parra-Vega, Vicente and S\'{a}nchez-Orta, Anand},

url = {https://academic.oup.com/imamci/article/34/2/597/2885232/Continuous-fractional-sliding-mode-like-control},

doi = {https://doi.org/10.1093/imamci/dnv064},

issn = {0265-0754},

year  = {2015},

date = {2015-00-00},

journal = {IMA Journal of Mathematic al Control and Information},

volume = {34},

abstract = {Exploiting algebraic and topological properties of differintegral operators as well as a proposed principle of dynamic memory resetting, a uniform continuous sliding mode controller for a general class of integer order affine non-linear systems is proposed. The controller rejects a wide class of disturbances, enforcing in finite-time a sliding regime without chattering. Such disturbance is of H\"{o}lder type that is not necessarily differentiable in the usual (integer order) sense. The control signal is uniformly continuous in contrast to the classical (integer order) discontinuous scheme that has been proposed for both fractional and integer order systems. The proposed principle of dynamic memory resetting allows demonstrating robustness as well as: (i) finite-time convergence of the sliding manifold, (ii) asymptotic convergence of tracking errors, and (iii) exact disturbance observation. The validity of the proposed scheme is discussed in a representative numerical study.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}