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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 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.

The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.

After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.

The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.

The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.

This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.

In the redesign process of assembly components that need adaptation to robotic assembly, designers can find support from structured methodologies for innovation, such as the theory of inventive problem solving (TRIZ). This paper aims to illustrate the authors’ methodology for redesigning gas hobs components for adaptation to robotic assembly.

A designer approaching a redesign task of an assembly component of any kind for adaptation to robotic assembly must consider, first of all, the features and limitations of existing robotic assembly systems; the generation of new design ideas that best fit the requirements may result to be a very challenging task. Here, the TRIZ methodology has proven useful for generating design ideas and finding the best solution.

The authors’ methodology approaches the challenges of redesign tasks for robotic assembly adaptation, which exploits knowledge of automatic and robotic assembly systems and the TRIZ method for innovation; it has proven useful in the redesign, checks and prototyping of gas hobs components.

This paper shows how the TRIZ methodology can be integrated into the redesign process and its impact on an industrial environment. The work’s main value is to provide a set of steps to help the designers change their design components approach that is necessary but not still implemented to optimize the use of the automation.

The purpose of the following work was to work out the dependency to allow for the determination of the repeatability positioning error value of the robot at any given point in its workspace, without the necessity of conducting time-consuming measurements while routing a precise surface of repeatability positioning.

The presented dependency permits for the possibility to determine, even at the planning phase, the optimal connection point in the workspace, ensuring the best parameters for the process of machine assembly, without needless overestimation of precision of the utilized equipment. To solve the task the sequential quadratic programming (SQP) method implemented in the MATLAB(R) environment was used. To verify the hypothesis of the compatibility of the empirical distribution with the hypothetical distribution of the robot’s positioning error, the Kolmogorov test was used.

In this paper, it has been demonstrated theoretically and experimentally that the industrial robot accuracy can vary over a very wide range in the workspace. This provides an additional opportunity to increase reliability of the assembly process through the appropriate choice of the point of parts joining. The methodology presented here allows the designer of assembly workstations to rapidly estimate the repeatability of robot positioning and to allocate at the design stage of assembly process the optimal position in the robot workspace to ensure the required precision, without unnecessarily high accuracy of equipment used and, therefore, without inflated costs.

An alternative solution to the stated problem can be the proposed method for determining the robot’s positioning errors, requiring a much smaller amount of measurements to be taken that would be necessary to determine the parameters of the random variable errors of the joint coordinates of the robot and for their verification by the repeatability of positioning in randomly selected points in the workspace. Additionally discussed in the study, the methodology of identifying connection place was designed for typical combinations of machine parts, most frequently encountered in assembly process and was taken into account, typical limitations occurring in actual manufacturing conditions.

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.

This paper aims to design a novel jaw gripper with human-sized anthropomorphic features to be suitable for precise in-hand posture transitions, such as twisting and re-positioning. The growing demand from traditional high-mix low-volume and new massive customized manufacturing industry requires the robot with configurability and flexibility. In the electronic manufacturing industry particularly, the design of the robotic hand with sufficient dexterity and configuration is important for the robot to accomplish the assembly task reliably and robustly. It is important for the robot to be able to grasp and manipulate a large number of assembly parts or tools.

In this research, a novel jaw-like gripper with human-sized anthropomorphic features is designed for online in-hand precise positioning and twisting. It retains the simplicity feature of traditional industrial grippers and dexterity features of dexterous robotic hands.

The gripper is able to apply suitable gripping force on assembly parts and performs reliable twisting movement within limited time to meet the industrial requirements. Manipulating several cylindrical assembly parts by robot, as an experimental case in this paper, is studied to evaluate its performance. The effectiveness of proposed gripper design and mechanical analysis is proved by the simulation and experimental results.

The main originality of this research is that a novel jaw gripper with human-sized anthropomorphic features is designed to be suitable for precise in-hand posture transitions, such as twisting and re-positioning. With this gripper, the robotic system will be sufficiently flexible to deal with various assembly tasks.

From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems.

In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer.

This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis.

The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries.

In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

The purpose of this paper is to develop an automated industrial robotic system for handling steel castings of various sizes and shapes in a foundry.

The authors first designed a prismatic gripper for pick-and-place operations that incorporates underactuated passive hydraulic contact (PHC) phalanges that enable the gripper to easily adapt to different casting shapes. The authors then optimized the gripper parameters and compared it to an adaptive revolute gripper using two methods: a planar physics based quasistatic simulation that accounts for object dynamics and validation using physical prototypes on a physical robot.

Through simulation, the authors found that an optimized PHC gripper improves grasp performance by 12 per cent when compared to an human-chosen PHC configuration and 60 per cent when compared to the BarrettHand™. Physical testing validated this finding with an improvement of 11 per cent and 280 per cent, respectively.

This paper presents for the first time optimized prismatic grippers which passively adapt to an object shape in grasping tasks.