A study on data-driven in-hand twisting process using a novel dexterous robotic gripper for assembly automation (original) (raw)
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Design of an industrial robotic gripper for precise twisting and positioning in high-speed assembly
In electronic manufacturing system, the design of the robotic hand is important for the successful accomplishment of the assembly task. Due to the restriction of the architecture of traditional robotic hands, it is difficult to grasp the cylinder shaped assembly parts with correct posture. In this research, a novel 4-DOF jaw like gripper is designed and built for precise positioning and twisting online. It can apply a constant gripping force on assembly parts and perform reliable twisting movement. Manipulating a cylinder shaped assembly part by robot, as an experimental case in this paper, is studied to evaluate the performance. The effectiveness of proposed gripper design and mechanical analysis is proved by the experiments.
Lecture Notes on Multidisciplinary Industrial Engineering, 2018
In today's era of mass customization, assembly automation systems should be designed with necessary production flexibility to cope with the growing product varieties to adapt to diverse customer requirements, yet the production costs should not be significantly different from those of comparable products made by mass production. In order to cope with this product variety-cost trade-off, robotics offers a flexible automation technology for turning assembly systems into efficient and flexible systems. Despite their great potential for high flexibility, there is a range of issues which must be addressed for its successful implementation. This chapter examines some of these key issues and challenges, reviews the results of previous research and describes our ongoing research on development of a flexible assembly system for mechanical products, using an industrial robot with machine vision guidance and dexterous multi-finger gripper. As part of the research work reported in this chapter, a Sexual Genetic Algorithm (SGA)-based approach for generation of optimal assembly sequence, a knowledge-based system for generating the robot task-level plan, a multi-finger robot gripper for flexible assembly based on a tendon-driven mechanism and an impedance control algorithm, and finally a strategy for implementation of robotic assembly under machine vision guidance have been presented.
Proposal of a shape adaptive gripper for robotic assembly tasks
Advanced Robotics, 2016
This paper proposes a novel robotic gripper used for assembly tasks that can adaptively grasp objects with different shapes. The proposed hand has a combined structure between two kinds of shape adaptive mechanisms where one is the granular jamming and the other is a multi-finger mechanism driven by a single wire. Due to the effect of the two shape adaptive mechanisms, the pose of a grasped object does not change during an assembly operation. The proposed hand has four fingers where two are the active ones and the other two are the passive ones. The pose of the grasped object can be uniquely determined since the passive fingers are used to orient an object placed on a table before the active fingers are closed to grasp it. Assembly experiments of some kinds of parts are shown to validate the effectiveness of our proposed gripper.
A gripper design algorithm for grasping a set of parts in manufacturing lines
Mechanism and Machine Theory, 2016
A simple gripper for a robotic arm capable of grasping various objects in manufacturing lines provides great benefits in terms of standardization of grippers, reducing engineering time and costs. This will provide the possibility to reuse the manufacturing line for several products of different geometry without significant changes. The goal is to make a gripper such that it will be a commodity similar to the robot arms. The algorithm, termed 3D-OCOG (3-Dimensional Objects COmmon Grasp search) and proposed in this paper, searches for a common grasp configuration over a set of spatial objects. It maps all possible grasps for each object that satisfy force closure and quality criteria so the grasps could counterbalance external wrenches (forces and torque) applied to the object. The mapped grasps are parameterized as feature vectors in a high-dimensional space. This feature vector describes the design of the gripper. A database of feature vectors is generated for all possible grasps for each object in the feature space. A similarity join based on nearest-neighbor search and classification algorithm are used for intersecting all possible feature vectors over all objects and finding common ones. Each feature vector found is a grasp configuration for the group of objects, which directly implies the gripper design. Simulations of a 3-finger grasp of four meshed objects resulted in several common grasp solutions. Therefore, a designated experimental setup was established composed of three robotic fingers, to simulate the grasp of the test objects. Results of the simulations and experiments validate the feasibility of the proposed algorithm.
The mechanical and control system design of a dexterous robotic gripper
ICECS 2001. 8th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.01EX483), 2001
The design and development of dexterous robotic end effectors has been an active research area for a long while. This paper reviews the design and construction of a versatile robotic gripper used to grasp objects of arbitrary shape, size and weight. This is achieved through a mechanical design that incorporates multiple fingers and multiple joints per finger, through the installation of proximity and force sensors on the gripper, and through the employment of an innovative and practical control system architecture for the gripper components. The gripper is installed on a standard six degree-of-freedom industrial robot, and the gripper and robot control programs are integrated in a manner that allows easy application of the gripper in an industrial pick-and-place operation where the characteristics of the object can vary or are unknown.
The BarrettHand grasper – programmably flexible part handling and assembly
Industrial Robot: An International Journal, 2000
This paper details the design and operation of the BarrettHand BH8‐250, an intelligent, highly flexible eight‐axis gripper that reconfigures itself in real time to conform securely to a wide variety of part shapes without tool‐change interruptions. The grasper brings enormous value to factory automation because it: reduces the required number and size of robotic workcells (which average US$90,000 each – not including the high cost of footprint) while boosting factory thoughput; consolidates the hodgepodge proliferation of customized gripper‐jaw shapes onto a common programmable platform; and enables incremental process improvement and accommodates frequent new‐product introductions, capabilities deployed instantly via software across international networks of factories.
Object Gripping With Automated Robotic Arm Movement
2018
In the upcoming era of advanced technology, for the ease of the human being living, industrial automation with lesser human effort and all other possible application areas are enriched with the ever growing features of technical advancement in the field of Robotic mechanism. In this project work the effort of restructuring an automated mechanical arm is depicted with the utilization of infrared obstruction detection and also relocation of that specific object. The incorporation of Arduino programming merged with the intelligent design approach of robotic movement of an artificial hand is the main attraction of the presented work. This gives the idea of a creation in technical field where hardware and software interfacing is done tactfully.
Grasp Planning for Customized Grippers by Iterative Surface Fitting
— Customized grippers have broad applications in industrial assembly lines. Compared with general parallel grippers, the customized grippers have specifically designed fingers to increase the contact area with the workpieces and improve the grasp robustness. However, grasp planning for customized grippers is challenging due to the object variations, surface contacts and structural constraints of the grippers. In this paper, an iterative surface fitting (ISF) algorithm is proposed to plan grasps for customized grippers. ISF simultaneously searches for optimal gripper transformation and finger displacement by minimizing the surface fitting error. A guided sampling is introduced to avoid ISF getting stuck in local optima and improve the collision avoidance performance. The proposed algorithm is able to consider the structural constraints of the gripper and plan optimal grasps in real-time. The effectiveness of the algorithm is verified by both simulations and experiments.
Design and modeling industrial intelligent robot flexible hand
Bulletin of Electrical Engineering and Informatics
The article describes a description of a fundamentally new design, mathematical model and experimental research of a flexible arm with an anthropomorphic gripper for an industrial robot. The advantage of the proposed design of the robot arm in comparison with the known traditional technical solutions is achieved as close as possible to the functions of the human arm. This property significantly increases the versatility of the robot arm when performing various technological operations. Another difference from the known models of industrial robots is the presence of an anthropomorphic gripping device in the flexible arm, which allows you to service products with different shapes and arbitrary coordinates in space. In addition, the article for the first time proposes a method for calculating the parameters of a new hand and experimental studies of its functioning, which will allow engineers in the field of robotics to create similar designs. The economic effect of the proposed design ...