Petar B. Petrovic

Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly

This paper presents a methodology for generating a fuzzy inference mechanism (FIM) for recognizing contact states within robotic part mating using active compliant motion. In the part mating process, significant uncertainties are inherently present. As a result it is pertinent that contact states recognition systems operating in such environment be able to make decisions on the contact state currently present in the process, based on data full of uncertainties and imprecision. In such conditions, implementation of fuzzy logic and interval inference brings significant robustness to the system. As a starting point for FIM generation, we use a quasi-static model of the mating force between objects. By applying Discrete Wavelet Transform to the signal generated using this model, we extract qualitative and representative features for classification into contact states. Thus, the obtained patterns are optimally classified using support vector machines (SVM). We exploit the equivalence of SVM and Takagi–Sugeno fuzzy rules based systems for generation of FIM for classification into contact states. In this way, crisp granulation of the feature space obtained using SVM is replaced by optimal fuzzy granulation and robustness of the recognition system is significantly increased. The information machine for contact states recognition that is designed using the given methodology simultaneously uses the advantages of creation of machine based on the process model and the advantages of application of FIM. Unlike the common methods, our approach for creating a knowledge base for the inference machine is neither heuristic, intuitive nor empirical. The proposed methodology was elaborated and experimentally tested using an example of a cylindrical peg in hole as a typical benchmark test.

Context sensitive recognition of abrupt changes in cutting process

This paper presents a new generic approach to real-time monitoring of abrupt changes in cutting process. Proposed method is based on hierarchical fuzzy clustering of patterns obtained from discrete wavelet transform (DWT) of acquired signals correlated with cutting force variation in time. Cutting process is naturally highly dynamical and normally consists of mixture of various dynamic phenomena related to the chip formation process and dynamical responses of machining system, workpiece and tool itself. These phenomena are characterized by different time duration. The class of phenomena related to abrupt changes during short time interval is of special importance since they correspond to the most dramatic changes in cutting process, such as various kinds of tool failure or workpiece damage or even breakage. Due to their short time duration, discovery and recognition of these phenomena is extremely difficult. To solve given problem we have chosen DWT, fuzzy clustering and finite state automata as a formal platform for its analysis. Beside its good time localization properties, DWT is, due to asymmetric and irregular shapes of wavelets, especially suitable for analysis of signals having sharp changes or even discontinuities. Given properties make DWT an efficient means for extraction of representative and reliable information contents, thus making good basis for extraction of discriminative and representative features (as DWT coefficients combinations) for classification that will follow. Robustness of specific pattern recognition and learning may be achieved only by taking into consideration wider context. Therefore, in tool condition pattern recognition we have considered the entire context of changes in cutting process state space that precedes and appears after the phenomenon which should be recognized. The cutting process behavior and its evolution in time are considered rather then momentary state which is represented as a point in adopted feature hyperspace of classification machine. Efficiency and practical applicability of developed method is evaluated by extensive experiments in laboratory conditions.

Recognition of Contact States in Robotized Assembly Using Qualitative Wavelet Based Features and Support Vector Machines

This paper presents a method for recognition of contact states in robotized assembly using an example of cylindrical peg into hole part mating. Starting from force quasi-static model, offline features extraction using Discrete Wavelet Transform and teaching (classification) using Support Vector Machines is carried out. Thus obtained class boundaries together with features extracted from signals of generated contact force vector are used for recognition of contact states on-line. Proposed method is tested using intensive real world experiments.

New Feeding System for High Speed Assembly of Small Parts

Abstract This paper presents the new general purpose automatic feeding system, developed for high speed assembly of small parts. The new design is a result of the consequently applied Axiomatic Design Theory. The feeding system is functionally uncoupled, leading to minimization of problems in system tuning, parts damage and noise emission. Moreover, the new design gives the possibility for simple introduction of additional functional modules such as: sensorized modules for non-geometrical orientation of parts, or active orientation modules for improving efficiency of the system. The proposed system is verified by the prototype developed for feeding screws on pneumatic screwdriving station.

Diagnosis of irregularities in the robotized part mating process based on contextual recognition of contact states transitions

Purpose – The purpose of this paper is to provide a method for the generation of information machines for part mating process diagnosis. Recognition of contact states between parts during robotized part mating represents a significant element of the system for active compliant robot motion. All proposed information machines for contact states recognition will recognize one of the possible contact states even when irregular events in the process occur, and the active motion planner will continue to send commands to robot controller according to the planned trajectory. Design/methodology/approach – The presented framework is based on the general theory of automata and formal languages. Starting from possible regular contact states transitions in part mating, the authors create an automaton for diagnostics, which, besides regular, accepts all irregular (observable and unobservable) process sequences. Findings – Contact states do not appear arbitrarily during regular processes, but in certain context. Theory ...

Closed-Form Resolution Scheme of the Direct Kinematics of Parallel Link Systems Based on Redundant Sensory Information

Abstract In this paper, the direct kinematics transformation in parallel link systems, based on redundant sensing approach is addressed. The redundant sensory information is provided by additional position sensors, connected directly to the parallel structure in a parallel manner. Optimization of position and the number of redundant sensors is performed by a proposed Geometrical-Structure-Partitioning Method. The efficiency of the method is verified by two examples — type 3-3 and 6-3 spatial structures, where only one redundant sensor is identified as sufficient for unique closed-form solution of the direct kinematics problem.

Activities of Euro-CASE Engineering Education Platform

A platform dedicated to the problems of engineering education (EngEdu) has been established by European Council of Academies of Applied Sciences, Technologies and Engineering (Euro-CASE). The renewed working group (WG) of this EngEdu Platform started to work in Sept. 2017 and now tries to establish a direct link with REV conference participants and organizers, and disseminate and exchange ideas and results. Current topics of interest are presented as well as one of the projects going on.

Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland). In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency–mimetic neuronal models, and can be useful for the design of high performance haptic devices.

Adaptive fuzzy control of mechanicalbehavior for a two degree-of-freedomrobotic manipulator

Active compliance control of robotic manipulators is useful in making robots perform precision assembly operations. The essential requirement here is mechanical isotropy of the robot end-point. In this paper the problem of how to achieve this kind of mechanical behaviour is considered from aspects of impedance control and fuzzy set theory. The new fuzzy–impedance control law, which is suitable for real-time applications, is proposed for a two degree-of-freedom (2-d.o.f.) robotic manipulator. According to simulation results, the proposed control law can provide approximately isotropic behaviour of the robot end-point in the whole workspace.

A Concept of an Intelligent Fuzzy Control for Assembly Robot

Abstract Active accommodation of robotic manipulator in assembly applications is considered. Mechanical impedance control concept has been chosen for development an intelligent controller for assembly robots, where target impedance appears as a control variable. Basic assumption for successful part mating process according to part mating theory is mechanical isotropy of support system. Consequently, target impedance should be adopted as isotropic. The main problem appearing here is complex analytical formulation of isotropic target impedance and uncertainty of parameters related to the robot and environment model. To overcome this problem an adaptive fuzzy model of isotropic target impedance is proposed. The fuzzy model is incorporated into general impedance control law form, to obtain new fuzzy-impedance control law. Proposed control law has been verified by computer simulation.