Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Inchworm robot grippers for clothes manipulation

Manipulating deformable objects like clothes, plastic, and paper by a robot is very challenging. This paper focuses on clothes manipulation as an example. A tracing manipulation method is used here to find a corner of the clothes. In this paper, tracing refers to tracing the clothes’ edge, with the robot’s movement based on feedback from sensors. One difficulty during this edge tracing is to make the robot trace smoothly and speedily without dropping the clothes in the process. This is due to the fact that deformable objects are sensitive to contact forces. A solution to this problem is to design a special robot gripper that can trace the clothes without having to worry about the clothes slipping away. In this paper, the development of inchworm-type grippers is proposed. Two sets of grippers inside a robot hand will allow the robot to trace the clothes more freely because there will always be a gripper firmly holding the clothes at any time. A unique tracing method for towel spreading using the inchworm grippers is also discussed. Experimental results have demonstrated the effectiveness of both the proposed grippers and also the algorithm. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Clothes Manipulation by Robot Grippers with Roller Fingertips

Unfolding or spreading is a very important process in clothes handling in order to sort out whether an item is a shirt, skirt, pants, etc. Spreading of clothes basically involves holding two corners of the clothes next to each other. The problem is finding the two corners. Usage of tracing manipulation to find the second corner can solve this problem. However, there are also problems concerning tracing manipulation. One of the major problems is how to retrieve the fabric when it is in danger of slipping away from the gripper. The robot may be able to detect that the fabric is about to slip, but it is hard to retrieve or prevent it. If the robot tries to regrasp the fabric, it would probably slip away. If the robot tries to retrieve the fabric without regrasping it, it would most probably drag the fabric along instead of retrieving it. This is due to the fact that deformable objects are sensitive to contact forces. A simple solution to this problem is to design a special gripper that can trace the edge smoothly and can also perform fabric retrieval. This paper proposes a unique tracing method for towel spreading using two sensors-equipped grippers with a rolling mechanism at the fingertips. Tracing in the context of this paper involves tracing the towel's edge, with the robot movement based on feedback from sensors. The gripper will allow more flexibility towards fabric manipulation. Experimental results have demonstrated the effectiveness of both the method and the grippers.     

Adaptive neuro fuzzy controller for adaptive compliant robotic gripper

The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult то control using conventional techniques. Here, a novel design of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling input displacement of a new adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Since the conventional control strategy is a very challenging task, fuzzy logic based controllers are considered as potential candidates for such an application. Fuzzy based controllers develop a control signal which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS controller, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.     

抓取任务中的融差控制方法

依据“融差性思维”,提出了无需精确感知依旧可以在一定范围内有效工作的融差控制方法。具体分析了融差抓取方法如何运用相同控制量实现不同抓取任务的工作原理,这一原理使得融差抓取方法在面对一大类抓取任务时,不需要知道物体的具体参数,只需要知道这一大类物体的边界条件。进一步分析了融差抓取方法在欠驱动手爪上的适用性,并发现了欠驱动手爪的局限性。实验表明,在控制量设定不变的情况下,依据融差抓取方法,柔性手爪可以抓住且不抓坏宽度范围为5～45 mm的嫩豆腐,且能够成功抓取宽度范围为5～60 mm的硬质长方体;弹簧关节欠驱动手爪可以抓住且不抓坏宽度范围为20～40 mm的嫩豆腐,且能够成功抓取宽度范围为5～60 mm的硬质长方体。这体现了融差抓取方法的通用性和欠驱动手爪在抓取柔性物体时的局限性。最后,展示了柔性手爪使用融差抓取方法在桌面抓取应用中以简单的控制策略成功抓取不同形状、不同材质的物体。这充分说明了融差抓取方法不依赖于精确的对象感知及物体模型,能够简化控制策略。     

Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper

The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult make decision strategies using conventional techniques. Here, an adaptive neuro fuzzy inference system (ANFIS) for controlling input displacement and object recognition of a new adaptive compliant gripper is presented. The grasping function of the proposed adaptive multi-fingered gripper relies on the physical contact of the finger with an object. This design of the each finger has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Fuzzy based controllers develop a control signal according to grasping object shape which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS strategy, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.     

Neural network approach to firm grip in the presence of small slips

This paper presents a two stage method for constructing a firm grip that can tolerate small slips of the fingertips. The fingers are assumed to be of frictionless contact type. The first stage was to formulate the interaction in the gripper–object system as a linear complementarity problem (LCP). Then it was solved using a special neural network to find minimal fingers forces. The second stage was to use the obtained results in the first stage as a static mapping in training another neural network. The second neural network training included emulating the slips by random noise in the form of changes in the positions of the contact points relative to the reference coordinate system. This noisy training increased robustness against unexpected changes in fingers positions. Genetic algorithms were used in training the second neural network as global optimization techniques. The resulting neural network is a robust, reliable, and stable controller for rigid bodies that can be handled by a robot gripper. © 2001 John Wiley & Sons, Inc.     

A flat surface robotic gripper for handling limp material

A prototype flat-surface, single-chambered and multi-chambered gripper, based on the operational principle of suction and pressure differential has been designed, implemented and experimentally tested. The prototype grippers are proven sufficient to pick and place fabric material accurately and reliably without causing any distortion and/or folding of the fabric. Both prototype grippers have been mounted on AdeptOne and AdeptThree robot arms for experimental and reliability analysis. They both meet requirements as set by the US apparel industry, related to pick and place single cut plies of several types of fabric     

A risc approach to sensing and manipulation

This article describes sensing and manipulation strategies that use simple, modular robot hardware. To bridge the gap between automation and robotic technologies, we suggest that traditional automation hardware, such as parallel-jaw grippers and optical beam sensors, can be combined with geometric planning and sensing algorithms. The resulting systems should be cost-effective, reliable, and easy to set up and reconfigure. They should also be flexible enough to support small batch sizes and rapid changes in part design needed in forthcoming flexible/agile manufacturing systems. The RISC acronym, borrowed from computer architecture, suggests the parallels between the two technologies. RISC robots perform complex operations by composing simple elements. The elements may be individual light beam sensors, grouped together to form an array for recognition. Or a complex manipulation task may be performed via a sequence of grasp steps by different grippers specialized for acquisition and placement. This article emphasizes three areas: (i) RISC sensing, primarily optical beam sensing, (ii) RISC manipulation using simple parallel-jaw grippers or minimal configurations of fingers, and (iii) Computer-aided design of RISC workcells. © 1995 John Wiley & Sons, Inc.     

Design and Realization of the Claw Gripper System of a Climbing Robot

Climbing robots are widely used to inspect smooth walls, such as glass curtain walls and ceramic tile surfaces. However, a good adsorption method for inspecting a cliff face and dusty high-altitude buildings with small-amplitude vibration has not been found. In this study, a new adsorption method using grasping claw grippers to adhere to rough walls is proposed and applied. A mechanical model for the interaction between the gripper and the uplifts on rough walls is also established to analyze the critical state of force balance of the gripper. In addition, MATLAB is used in a simulation, and an experimental prototype is designed to test the grasp stability of the gripper. Simulation and experiment results indicate that the gripper can adequately achieve grasping adsorption on a rough concrete wall. The findings provide a foundation for constructing a system for a rough-wall-climbing robot.     

Adaptive neuro-fuzzy prediction of grasping object weight for passively compliant gripper

The development of universal grippers able to pick up unfamiliar objects of widely varying shapes and surfaces is a very challenging task. Passively compliant underactuated mechanisms are one way to obtain the gripper which could accommodate to any irregular and sensitive grasping objects. The purpose of the underactuation is to use the power of one actuator to drive the open and close motion of the gripper. 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 iterative finite element method (FEM) optimization procedure. The main points of this paper are in explanation of a new sensing capability of the gripper for grasping and lifting up the gripping objects. Since the sensor stress depends on weight of the grasping object it is appropriate to establish a prediction model for estimation of the grasping object weight in relation to sensor stress. A soft computing based prediction model was developed. In this study an adaptive neuro-fuzzy inference system (ANFIS) was used as soft computing methodology to conduct prediction of the grasping objects weight. The training and checking data for the ANFIS network were obtained by FEM simulations.     

Anisotropically etched silicon fibre-grippers

High precision vacuum grippers for optical fibre components are fabricated by silicon bulk micromachining. Anisotropic etching of (100) and (110) silicon wafers offers high precision and lower fabrication costs than deep reactive ion etching (D-RIE) processes. Two types of grippers are introduced: a vertical, narrow one for chips where space is limited and short fibre elements have to be assembled. For longer fibres and high angular precision a horizontal gripper with multiple gripper ledges is presented.     

Team O2AS' approach for the task-board task of the World Robot Challenge 2018

ABSTRACT

In this paper, we describe the approach of Team O2AS to complete the task-board task of the World Robot Challenge 2018, held in Tokyo. We use a custom gripper and graspable tools with in-built compliance to work with various kinds of parts, increase robustness against uncertainties, and to avoid complicated control strategies. The robots are able to finish all the sub-tasks without the need to exchange grippers. The main idea is to use mechanical compliance and self-centering mechanisms to deal with uncertainty. This is achieved by aligning the objects using either the gripper and tools, or by the design of the robot motions.     

Synthesizing two-fingered grippers for positioning and identifyingobjects

Most industrial grippers now in use are two-fingered. Among them the parallel-jaw gripper is the simplest. It can partially remove the pose uncertainty of an object through grasping, such as the orientation uncertainty. This paper addresses a new type of grippers with the finger configuration of four circles instead of two parallel lines. It has a number of important advantages. Especially, it achieves form-closure and confines the object to a locally unique pose, so as to remove the pose uncertainty completely. It allows the gripped object to reach this pose freely without loss of required friction in the direction perpendicular to the grasping plane. More information can be acquired for identifying the object and its grasp mode. As a result the identification can be performed at one grasp. The key parameter of a symmetric four-pin gripper is the distance (span) between two pin centers on each finger, which depends upon the object shape and impacts the closure property, Based on a new approach to the grasp geometry, selection and limitations of the span are illustrated.     

Proposal of a shape adaptive gripper for robotic assembly tasks

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.     

Development of a new noncontact gripper using swirl vanes

In this paper, we proposed a new noncontact gripper called as swirl gripper. It generates swirling air flow to create an upward lifting force. This force can be used to pick up a work piece placed underneath the swirl gripper without any contact. In comparison with conventional pneumatic noncontact grippers, the uniqueness of the new gripper lies in that it is electrically (rather than pneumatically) activated. We carry out this study for clarifying the mechanism of the swirl gripper. First, we show the design of the swirl gripper and briefly illustrate the mechanism by which it forms a negative pressure to create a lifting force. Then, we experimentally investigate the characteristics of the pressure distribution, based on which a theoretical analysis on the swirling flow is conducted. Furthermore, we measure the relationship between the lifting force and gap clearance and reveal that there exists a levitation zone where a work piece can maintain a stable levitation. Finally, we verify the practicability by successfully noncontact handling a Φ300 mm silicon wafer with four swirl grippers.     

A servo-controlled robot gripper with multiple sensors and its logical specification

The logical specification of a microprocessor-based air-servo-controlled robot hand is presented, as well as its actual implementation. This hand can accommodate a wide variety of workpieces and allows for flexible assembly through the use of an automatic quick-change fingertip. The changeable set of gripper fingers is equipped with sensors, including a tactile force sensor, a crossfire sensor, a proximity sensor, and a slip sensor. A changeable set of gripper fingers with different sensing ranges can cope with certain subranges of the workpiece spectrum. A considerable cost saving is achieved by not changing the gripper itself. This specially designed hardware and software system includes position and force feedback. A PUMA 560 is used to test the success of the entire process.     

Force-closed grasping with two hands

Two-handed grasping of rigid objects in two-dimensional space is studied. The hands considered in this article are either flat-surface palms or grippers with two angular-motion fingers. Presented in this article is a condition that establishes the existence of force-closed grasping without the knowledge of the shape of the grasped object and of the exact contact locations on the palms or fingers. Further, an algorithm is developed that determines force-closed grasping based on the position and orientation of the two hands.     

SCARA based peg-in-hole assembly using compliant IPMC micro gripper

Robotic assembly is difficult as there always exist position errors between two mating parts. Compliance is added in a selective compliant assembly robot arm (SCARA) in the form of a two ionic polymer metal composite (IPMC) fingers based micro gripper. This micro gripper is integrated at the end effector position of a SCARA robot. Peg-hole interaction is analytically modeled and based on it the force required to correct the lateral and angular errors by IPMC is calculated. A proportional-derivative (PD) controller is designed to actuate the IPMC to get the desired force for correcting the peg position before assembly. Simulations and experiments were carried out by developing an IPMC micro gripper and using it to analyze various cases of peg in hole assembly. The experimental results prove that adding compliance through IPMC helps in peg-in-hole assembly.     

单自由度转动式对心机械夹持器

近年来许多学者提出了各种新型的机械夹持器,对心夹持器就是其中的一种.现有的对心机械夹持器的主要缺点是结构复杂,设计麻烦,加工困难,夹持范围小.本文提出一种新的结构简单,制造容易,使用方便,夹持范围大,对心夹持精度高,能对心夹持各种圆柱体的转动式机械夹持器.这种夹持器是根据同心圆在同一圆心角下的不同圆上的弦相互平行的几何关系和平行四杆机械的运动特点设计的.夹持器的每侧是由摇杆滑块机构外接平行四杆机构组成的.