Speed-accuracy characteristics of human-machine cooperative manipulation using virtual fixtures with variable admittance

This work explores the effect of virtual fixture admittance on the performance, defined by error and time, of task execution with a human-machine cooperative system. A desired path is obtained using computer vision, and virtual fixtures for assistance in planar path following were implemented on an admittance-controlled robot. The admittance controller uses a velocity gain, so that the speed of the robot is proportional to the force applied by the operator. The level of virtual fixture guidance is determined by the admittance ratio, which is the ratio of the admittance gain of the force components orthogonal to the path to the gain of the force components parallel to the path. In Experiment 1, we found a linear relationship between admittance ratio and performance. In Experiment 2, we examined the effect of admittance ratio on the performance of three tasks: path following, off-path targeting, and obstacle avoidance. An algorithm was developed to select an appropriate admittance ratio based on the nature of the task. Automatic admittance ratio tuning is recommended for next-generation virtual fixtures. Actual or potential applications of this research include surgery, assembly, and manipulation at the macro and micro scales.     

Formal probabilistic analysis of a surgical robot control algorithm with different virtual fixtures

Surgical robots are increasingly being used in operation theaters involving normal or laparoscopic surgeries. The working of these surgical robots is highly dependent on their control algorithms, which require very rigorous analysis to ensure their correct functionality due to the safety-critical nature of surgeries. Traditionally, safety of control algorithms is ensured by simulations, but they provide incomplete and approximate analysis results due to their inherent sampling-based nature. We propose to use probabilistic model checking, which is a formal verification method, for quantitative analysis, to verify the control algorithms of surgical robots in this paper. As an illustrative example, the paper provides a formal analysis of a virtual fixture control algorithm, implemented in a neuro-surgical robot, using the PRISM model checker. In particular, we provide a formal discrete-time Markov chain-based model of the given control algorithm and its environment. This formal model is then analyzed for multiple virtual fixtures, like cubic, hexagonal and irregular shapes. This verification allowed us to discover new insights about the considered algorithm that allow us to design safer control algorithms.     

Evaluation of virtual fixtures for a robot programming by demonstration interface

We investigate the effectiveness of several types of virtual fixtures in a robot programming by demonstration interface. We show that while all types of virtual fixtures examined yield a significant reduction in the number of errors in tight tolerance peg-in-hole tasks, color and sound fixtures generally outperform a tactile fixture in terms of both execution time of successful trials and error rate. We have found also that when users perceive that the task is very difficult but the system is providing some help by means of a virtual fixture, they tend to spend more time trying to achieve a successful task execution. Thus, for difficult tasks the benefits of virtual fixturing are better reflected in a reduction of the error rate than in a decreased execution time. We conjecture that these trends are related to the limitations of currently available interfaces for human-robot interaction through virtual environments and to the different strategies adopted by the users to cope with such limitations in high-accuracy tasks.     

Planning for Modular and Hybrid Fixtures

Fixturing encompasses the design and assembly of fixtures to locate and hold a workpiece during a manufacturing operation such as machining or assembly. We have implemented an automated design algorithm for a fixturing toolkit called the fixture vise; the fixture vise involves two fixture plates mounted on jaws of a vise and modular fixturing elements (pegs or flatted pegs). Generally, a fixture vise can handle appropriately sized prismatic workpieces in many different ways. The design algorithm runs in O(A) time, where A is the number of configurations achieving simultaneous contact between the modeled object and four fixture elements; since simultaneous contact is a necessary but not sufficient precondition for force closure, A provides an upper bound on the number of force closure fixture configurations. Received June 6, 1994; revised November 17, 1994, February 1, 1995, February 28, 1995, and July 11, 1995.     

The application of neural networks in fixture planning by pattern classification

The objective of this paper is to study the fixture planning of modular fixtures for cutting by means of a computer-aided fixture system (CAFS). The fixture planning presented here integrates the database of modular fixtures, neural networks, the heuristic algorithm of fixture position and the use of Advanced Modelling Extension Release 2.1 (AME) of AutoCAD R12 as the 3D graphic interface. The function suitable for the AME environment was also controlled to obtain detailed data of the geometry and topology of the workpiece to develop the fixture planning for modular fixtures. First of all, the concept of group technology (GT) was used to establish the coding database of the modular fixture element for use in the system. This paper presents fixture planning which combines the pattern recognition capability of the neural networks and the concept of GT to group the workpieces with different patterns but identical fixture modes into the same group. After network training, the fixture mode of the workpiece to be clamped can be inferred, and the selection of the fixture elements can be completed.     

A desktop virtual reality-based interactive modular fixture configuration design system

Modular fixture configuration design is a complicated task requiring strong professional background and practical experience. However, automated or semi-automated computer aided modular fixture systems based on CAD packages still are not well accepted by the manufacturing industry due to the lack of intuitive interaction and immediate feedback compared with traditional models such as paper and physical models. In this paper, a novel Virtual Reality-based system for interactive modular fixture configuration design is presented. We use a multi-view based modular fixture assembly model to assist information representation and management. In addition, the suggested strategy is compatible with the principles of virtual environment and it is easy to reutilize the element model. Based on geometric constraints, we propose a precise 3D manipulation approach to improve intuitive interaction and accurate 3D positioning of fixture components in virtual space. Thus, the modular fixture configuration design task can precisely be performed in virtual space.     

Fault detection and prognosis of assembly locating systems using piezoelectric transducers

Fixture faults have been identified as a principal root cause of defective products in assembly lines; however, there exists a lack of fast and accurate monitoring tools to detect fixture fault damage. Locating fixture damage causes a decrease in product quality and production throughput due to the extensive work required to detect and diagnosis a faulty fixture. In this paper, a unique algorithm is proposed for fixture fault monitoring based on the use of autoregressive models and previously developed piezoelectric impedance fixture sensors. The monitoring method allows for the detection of changes within a system without the need for healthy references. The new method also has the capability to quantify deterioration with respect to a calibrated value. Deterioration prognosis can then be facilitated for structural integrity predictions and maintenance purposes based on the quantified deterioration and forecasting algorithms. The proposed robust methodology is proven to be effective on an experimental setup for monitoring damage in locating fixtures. Fixture wear and failure are successfully detected by the methodology, and fixture structural integrity prognosis is initiated.     

Case based reasoning method for computer aided welding fixture design

This paper presents a case-based reasoning (CBR) method for welding fixture design, a critical issue in the manufacturing of large and complicated equipment. However, previous fixture design research has mainly focused on machining fixtures rather than welding fixtures. In this paper, an approach of data abstraction for fixture design information representation is proposed, first to systemize and manage myriads of fixture related resources, e.g., past fixture design solutions, fixture units depository. Based on this approach, a multi-level CBR method for welding fixture design is then presented. This method could help designers, by referencing previous design cases, to make a conceptual fixturing solution quickly and, finally, finish the detailed solution of fixture design.     

力反馈柔性虚拟夹具辅助遥操作

针对未知环境遥操作的操作安全性与操作性能之间相互矛盾的问题,提出并实现一种力反馈柔性虚拟夹具方法.该方法通过引入柔性系数调节机器人倾向于期望运动方向的程度,将离线任务规划与操作者手动控制的优势相结合,在获得一定的操作性能的同时,具有避开离线任务规划路径中障碍的能力,保证了遥操作的安全性.在此基础上,将虚拟力反馈方法融合...     

Towards the design and development of a knowledge-based universal modular jigs and fixtures system

Jigs and fixtures are one of the important aspects of manufacturing. Parts may have different sets of fixturing requirements and call for different design strategies. Although there are numerous possibilities for fixture designs, a few basic configurations are clearly identifiable. Computer aided design (CAD) has done a little in assisting designers to design jigs and fixtures, making decisions of the best design selection, and providing designers with suggestions. The goal of this paper is to develop and document the design parameters and specifications utilized in jigs and fixtures design using universal modular jigs and fixtures design system (UMJFS). This is the first step to develop a knowledge-based Jigs and Fixture design and selection system. This application has the advantages of making the fixture design information completely modular and transparent, providing better match to the working conditions, reducing lead-time, and generally providing a significant enhancement of fixture productivity and economy. UMJFS has different standard and modular elements. This makes jigs and fixtures elements interchangeable and reusable. Designing a UMJFS then becomes a task of selecting and assembling the proper elements together.     

Online task recognition and real-time adaptive assistance for computer-aided machine control

Segmentation and recognition of operator-generated motions are commonly facilitated to provide appropriate assistance during task execution in teleoperative and human-machine collaborative settings. The assistance is usually provided in a virtual fixture framework where the level of compliance can be altered online, thus improving the performance in terms of execution time and overall precision. However, the fixtures are typically inflexible, resulting in a degraded performance in cases of unexpected obstacles or incorrect fixture models. In this paper, we present a method for online task tracking and propose the use of adaptive virtual fixtures that can cope with the above problems. Here, rather than executing a predefined plan, the operator has the ability to avoid unforeseen obstacles and deviate from the model. To allow this, the probability of following a certain trajectory (subtask) is estimated and used to automatically adjusts the compliance, thus providing the online decision of how to fixture the movement.     

Quality prediction and compensation in multi-station machining processes using sensor-based fixtures

New fixture technologies, such as sensor-based fixtures, will significantly improve part quality through cutting-tool path compensations in multi-station machining processes (MMPs). Successful application of sensor-based fixtures depends on the development of new variation reduction methodologies to predict part quality in MMPs and detect the critical machining stations whose critical manufacturing variations can be estimated by installing a suitable sensor-based fixture. In this paper, a methodology is proposed to facilitate the implementation of sensor-based fixtures in MMPs. This methodology involves three key steps: (1) an identification of station-induced variations; (2) a sensor placement optimization method for designing sensor-based fixtures; and (3) a compensability analysis. A case study is conducted to demonstrate the effectiveness of the methodology.     

Real-Time Segmentation of Plants and Weeds

This paper describes a real-time implementation of an algorithm to segment plants, weeds, and soil in images used to control an autonomous crop protection vehicle. We show how the segmentation module fits in to the overall system and mention previous work on other modules. We then describe a segmentation algorithm and show how it is implemented on two digital signal processors (DSPs) controlled by a single transputer. We present timing information to show that the algorithm can provide data at 5 Hz, which is fast enough to control the vehicle.     

A virtual fixture using a FE-based transformation model embedded into a constrained optimization for the dimensional inspection of nonrigid parts

Virtually mounting nonrigid parts onto their fixture is proposed by researchers to remove the need for the use of complex physical inspection fixtures during the measurement process. Current approaches necessitate the pre-processing of the free-state nonrigid part’s point cloud into a suitable finite element (FE) mesh and are limited by the use of the boundary conditions setting methods available in FE software. In addition to these limits, these approaches do not take into account the forces used to restrain the part during the inspection, as commonly mandated for aerospace panels. To address these shortcomings, this paper presents a virtual fixture method that predicts the fixed shape of the part without the aforementioned drawbacks of current approaches. This is achieved by embedding information retrieved from a FE analysis of the nominal CAD model into a boundary displacement constrained optimization. To evaluate the proposed method, two case studies on physical parts are performed using the proposed virtual fixture method to evaluate the profile and assembly force specifications of each part.     

Computer-aided analysis of reconfigurable fixtures and sheet metal parts for robotic drilling

This paper presents an automated manufacturing system for drilling sheet metal parts. All stand-alone systems such as the robot, a set of reconfigurable fixtures and the CAD/CAM workstation have been integrated into a flexible manufacturing system. This system analyzes and evaluates a given fixturing layout and assembles the reconfigurable fixtures automatically using a robot manipulator. An optimum fixturing layout and assembly are achieved by examining the workpart from a stress-strain point of view. In addition, issues such as geometric constraints, yielding and buckling, database design, collision detection, fixturing sequential control and the automatic assembly of fixture elements are considered. The computational and analytical concepts for the reconfigurable fixturing and drilling system are also presented in this paper.     

Concurrent engineering with delta files

We describe a test system in which we used a data management system and delta files to communicate engineering changes between two modeling systems: an ACIS-based solid modeling system running on a Sun Sparc workstation to create a part, and a CATIA system running on an IBM RS/6000 to design a fixture for it. The test system communicates the first version of the MBB part between the two engineers as a PDES/STEP (Product Data Exchange Standard/Standard for the Exchange of Product-Model Data) exchange file. The ACIS engineer then makes an engineering change to the part, thus creating, the second version (V2) of it, and a delta file communicates the V2 changes to the CATIA engineer. The CATIA engineer can use this delta file to highlight the changes to the part between the two versions. Although our test system/scenario is simple, it demonstrates the advantages of delta files. It also helped us identify several important issues for developing the method further. We first outline the STEP standard and how we used it to implement data exchange in our test system, then we discuss delta files and describe how we implemented them. We conclude with a discussion of the lessons learned from the test system and scenario     

An efficient algorithm for computing object poses in a modular fixture or gripper

Modular or reconfigurable fixtures (or grippers) can reduce manufacturing costs and time remarkably. Computing the poses of a given object in a modular fixture is a basic but tedious technique for designing and using such fixtures. This article presents an efficient algorithm for computing the poses. Starting from a unified expression of the outline of an object, this algorithm searches all matching poses automatically. If the outline consists of straight lines and circular arcs only, all the unknown variables can be calculated sequentially by substituting known (or tentative) data in respective expressions, without solving complicated simultaneous equations. When applied to arbitrary outlines, it involves nothing more than common interpolation. The search process is visualized through diagrams that clearly display the occurrence of matching poses. The computer programs are universally applicable. Only the data of the object outline and the fixture configuration need be input. Case studies show that the programs run fast and yield accurate results. © 2002 Wiley Periodicals, Inc.     

Constructing Virtual Cities by Using Panoramic Images

Simultaneously acquired omni-directional images contain rays of 360 degree viewing directions. To take advantage of this unique characteristic, we have been developing several methods for constructing virtual cities. In this paper, we first describe a system to generate the appearance of a virtual city; the system, which is based on image-based rendering (IBR) techniques, utilizes the characteristics of omni-directional images to reduce the number of samplings required to construct such IBR images. We then describe a method to add geometric information to the IBR images; this method is based on the analysis of a sequence of omni-directional images. Then, we describe a method to seamlessly superimpose a new building model onto a previously created virtual city image; the method enables us to estimate illumination distributions by using an omni-directional camera. Finally, to demonstrate the methods' effectiveness, we describe how we implemented and applied them to urban scenes.     

Intelligent Fixture Design through a Hybrid System of Artificial Neural Network and Genetic Algorithm

In designing fixtures for machining operations, clamping scheme is a complex and highly nonlinear problem that entails the frictional contact between the workpiece and the clamps. Such parameters as contact area, state of contact, clamping force, wear and damage in the contact area and deformation of the component are of special interest. A viable fixture plan must include the optimum values of clamping forces. Along research efforts carried out in this area, this comprehensive problem in fixture design needs further investigation. In this study, a hybrid learning system that uses nonlinear finite element analysis (FEA) with a supportive combination of artificial neural network (ANN) and genetic algorithm (GA) is discussed. A frictional model of workpart–fixture system under cutting and clamping forces is solved through FEA. Training and querying an ANN takes advantage of the results of FEA. The ANN is required to recognize a pattern between the clamping forces and state of contact in the workpiece–fixture system and the workpiece maximum elastic deformation. Using the identified pattern, a GA-based program determines the optimum values for clamping forces that do not cause excessive deformation/stress in the component. The advantage of this work against similar studies is manifestation of exact state of contact between clamp elements and workpart. The results contribute to automation of fixture design task and computer aided process planning (CAPP).