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The paper aims to discuss a new design methodology for multi-fingered robotic grippers.

Optimization of the compliant mechanism with underactuation.

A new robotic gripper principle without active control.

Design of multi-fingered robotic gripper as a monolithic structure without joints.

Passively compliant underactuated mechanisms are one way to obtain the gripper which could accommodate to any irregular and sensitive grasping object. The purpose of the underactuation is to use less active inputs than the number of degrees of freedom of the gripper mechanism to drive the open and close motion of the gripper. Another purpose of underaction is to reduce the number of control variables.

The underactuation can morph shapes of the gripper to accommodate different objects. As a result, the underactuated grippers require less complex control algorithms. The fully compliant mechanism has multiple degrees of freedom and can be considered as an underactuated mechanism.

This paper presents a new design of the adaptive underactuated compliant gripper with distributed compliance. The optimal topology of the gripper structure was obtained by optimality criteria method using mathematical programming technique. Afterwards, the obtained model was improved by iterative finite element optimization procedure. The gripper was constructed entirely of silicon rubber.

The main points of this paper are the explanation of the development and production of the new compliant gripper structure.

Tactile sensing is the process of determining physical properties and events through contact with objects in the world. The purpose of this paper is to establish a novel design of an adaptive neuro-fuzzy inference system (ANFIS) for estimation of contact position of a new tactile sensing structure.

The major task is to investigate implementations of carbon-black-filled silicone rubber for tactile sensation; the silicone rubber is electrically conductive and its resistance changes by loading or unloading strains.

The sensor-elements for the tactile sensing structure were made by press-curing from carbon-black-filled silicone rubber. The experimental results can be used as training and checking data for the ANFIS network.

This system is capable to find any change of contact positions and thus indicates state of the current contact location of the tactile sensing structure. The behavior of the use silicone rubber shows strong non-linearity, therefore, the sensor cannot be used for high accurate measurements. The greatest advantage of this sensing material lies in its high elasticity.

The essence of the conceptual design is getting the innovative projects or ideas to ensure the products with best performance. It has been proved that the theory of inventive problem solution (TRIZ) is a systematic methodology for innovation. The purpose of this paper is to illustrate the design of an adaptive robotic gripper as an engineering example to show the significance and approaches of applying TRIZ in getting the creative conceptual design ideas.

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shapes and surfaces is a very challenging task. The requirement for new adaptive grippers is the ability to detect and recognize objects in their environments.

The main aim of this work is to show a systematic methodology for innovation as an effective procedure to enhance the capability of developing innovative products and to overcome the main design problems. The TRIZ method will be utilized in order to eliminate the technical contradictions which appear in the passively adaptive compliant robotic gripper.

The design of an adaptive robotic gripper as an engineering example is illustrated in this paper to show the significance and approaches of applying TRIZ in getting the creative conceptual design ideas.

The purpose of this paper is to propose a new methodological framework within which a compliant robotic joint can be studied.

A new method is presented for detecting the direction of the robotic joint rotation when subjected to an external collision force.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor‐elements cannot be used for accurate measurements.

A new type of safe robotic mechanisms with an internal measuring system is proposed in this paper.

The aim of this paper is to investigate implementations of carbon‐black filled silicone rubber for tactile sensation.

The sensor‐elements for this tactile sensing structure were made by press‐curing from carbon‐black filled silicone rubber.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor cannot be used for accurate measurements. The greatest advantage of this material lies in its high elasticity.

A new method for artificial tactile sensing skin for robotic applications.

The purpose of this study is to establish a vibration prediction of pellet mills power transmission by artificial neural network. Vibration monitoring is an important task for any system to ensure safe operations. Improvement of control strategies is crucial for the vibration monitoring.

As predictive control is one of the options for the vibration monitoring in this paper, the predictive model for vibration monitoring was created.

Although the achieved prediction results were acceptable, there is need for more work to apply and test these results in real environment.

Artificial neural network (ANN) was implemented as the predictive model while extreme learning machine (ELM) and back propagation (BP) learning schemes were used as training algorithms for the ANN. BP learning algorithm minimizes the error function by using the gradient descent method. ELM training algorithm is based on selecting of the input weights randomly of the ANN network and the output weight of the network are determined analytically.

The purpose of this paper is to propose an extensible framework for extracting data set usage from research articles.

The framework uses a training set of manually labeled examples to identify word features surrounding data set usage references. Using the word features and general entity identifiers, candidate data sets are extracted and scored separately at the sentence and document levels. Finally, the extracted data set references can be verified by the authors using a web-based verification module.

This paper successfully addresses a significant gap in entity extraction literature by focusing on data set extraction. In the process, this paper: identified an entity-extraction scenario with specific characteristics that enable a multiphase approach, including a feasible author-verification step; defined the search space for word feature identification; defined scoring functions for sentences and documents; and designed a simple web-based author verification step. The framework is successfully tested on 178 articles authored by researchers from a large research organization.

Whereas previous approaches focused on completely automated large-scale entity recognition from text snippets, the proposed framework is designed for a longer, high-quality text, such as a research publication. The framework includes a verification module that enables the request validation of the discovered entities by the authors of the research publications. This module shares some similarities with general crowdsourcing approaches, but the target scenario increases the likelihood of meaningful author participation.

Having the discrepancies between different descriptions of an organic food consumer profile in various researches worldwide as well as the causes of their emergence as a starting point, the purpose of this paper is to apply the method of preference-based market segmentation (by means of conjoint and cluster analysis) to Serbian organic food market, searching for advantages of using that methodological approach and deepening knowledge about specific organic food market.

The research was conducted from May to July 2014 with 400 respondents participating (aged 18-30). Primary data were gathered by means of focus groups and a survey – structured personal interviews by using a questionnaire.

When applying conjoint and cluster analysis to data about Serbian consumers’ preferences towards researched product, it is possible to identify a segment that prefers organic food the most. Compared to other segments, these consumers are predominantly female, somewhat more mature, with the highest proportion of employed and near the top by the percentage of respondents who are married and have children. They strongly value the importance of diet for health, a number of them have experience with a disease of a close person, which is believed that could be prevented by proper diet, but they do the least sports.

The authors give managerial recommendations to actors operating at domestic organic food market.

According to the authors’ knowledge, the first application of preference-based market segmentation by conjoint and cluster analysis to organic food market, performed in Serbia, generally characterised by scarce food consumer research.