An ActiveVision System for Recognition of Pre-Marked Objects

Abstract -In this paper, a new 3D-object-recognition method for robotic assembly workcells is presented. The proposed method is focused on two basic concepts, namely active vision and object preconditioning. The paper will briefly present the main aspects of the proposed system. The Proposed Recognition Method [l] Herein, it is proposed to model an object using only a small number of 2D topologically-distinct perspective views. These are referred to as standardviews, each with a corresponding standard-view-axis. For successful recognition purposes, the input image of' an object must be one of its standard perspective views. Thus, a mobile camera is used, such that its optical axis can be aligned with one of the standardview-axes of the object in order to acquire a standardview. Then, the matching process is performed between h e acquired 2D standard-view of the object and the library of 2D standard-views of a set of objects. To enable the vision system to acquire standardviews, standard-view-axes must be pre-defined. This can be accomplished by defining a local surface normal for each distinct view of an object. The local surface normals can be defined by pre-marking the objects using circular markers. In the context of the above scheme, active vision is used for two purposes: (1) Acquiring only specific views of an object (i.e., standard views) by controlling the external parameters of the camera; and (2) Acquiring additional images (standard views) if needed by virtuc of the possibility that the recognition process is not successful after the analysis of the first image, either due to significant distortion and noise, or, insufficient visual information in the image initially acquired. On the other hand, object pre-marking, servcs the following purposes: (1) Specifying a set of object surfaces to be viewed; (2) Defining a local surface normal --a standard axis-of-view --(which can be cstimatcd from the shape of a marker in the imagc plane); and (3) Conveying local 3D orientation and 3D position of a surface of an object, which can be subsequently used for 3D-location estimation of the objcct with respect to a refercnce frame. Based on the above scheme, the major steps for the identification and 3D-location estimation of a premarked object can be listed as follows: In the context of on-line issues and system implementation, the following aspects of the new technique have been addressed: a sequential distortioncompensation procedure, marker boundary detection to a sub-pixel accuracy, elliptical parameter estimation [71, and 3D-location estimation of circular markers [8]. For a complete presentatior? of each of the above issues and the proposed solution method and experimental results, please refer to the corresponding refcrences indicated above. An Experimental Prototype of the Active-Vision System [3] In an attempt to verify the validity and performance of the presented active object recognition technique, a prototype of the system was developed. The prototype is able to recognize the idcntity of manufactured objects which appear randomly oriented in thc field of view of a camera, provided that the standard views of all objects are available and stored in a standard-view database. In this particular implementation, the functions of the active object recognition are distributed between a loosely-coupled vision subsystem and robot-control subsystem. The system is an integration of the follow

The Archimedes 2 mechanical assembly planning system

We describe the implementation and performance of Archimedes 2, an integrated mechanical assembly planning system. Archimedes 2 includes two planners, two assembly sequence animation facilities, and an associated robotic workcell. Both planners use full 3 dimensional data. A rudimentary translator from high level assembly plans to control code for the robotic workcell has also been implemented. We can translate data from a commercial CAD system into input data for the system, which has allowed us to plan assembly sequences for many industrial assemblies. Archimedes 2 has been used to plan sequences for assemblies consisting of 5 to 109 parts. We have also successfully taken a CAD model of an assembly, produced an optimized assembly sequence for it, and translated the plan into robot code, which successfully assembles the device specified in the model

Worker-robot cooperation and integration into the manufacturing workcell via the holonic control architecture

Cooperative manufacturing is a new field of research, which addresses new challenges beyond the physical safety of the worker. Those new challenges appear due to the need to connect the worker and the cobot from the informatics point of view in one cooperative workcell. This requires developing an appropriate manufacturing control system, which fits the nature of both the worker and the cobot. Furthermore, the manufacturing control system must be able to understand the production variations, to guide the cooperation between worker and the cobot and adapt with the production variations.Die kooperative Fertigung ist ein neues Forschungsgebiet, das sich neuen Herausforderungen stellt. Diese neuen Herausforderungen ergeben sich aus der Notwendigkeit, den Arbeiter und den Cobot aus der Sicht der Informatik in einem kooperativen Arbeitsplatz zu verbinden. Dies erfordert die Entwicklung eines geeigneten Produktionskontrollsystems, das sowohl der Natur des Arbeiters als auch der des Cobots entspricht. Darüber hinaus muss die Fertigungssteuerung in der Lage sein, die Produktionsschwankungen zu verstehen, um die Zusammenarbeit zwischen Arbeiter und Cobot zu steuern

LDRD final report: Automated planning and programming of assembly of fully 3D mechanisms

This report describes the results of assembly planning research under the LDRD. The assembly planning problem is that of finding a sequence of assembly operations, starting from individual parts, that will result in complete assembly of a device specified as a CAD model. The automated assembly programming problem is that of automatically producing a robot program that will carry out a given assembly sequence. Given solutions to both of these problems, it is possible to automatically program a robot to assemble a mechanical device given as a CAD data file. This report describes the current state of our solutions to both of these problems, and a software system called Archimedes 2 we have constructed to automate these solutions. Because Archimedes 2 can input CAD data in several standard formats, we have been able to test it on a number of industrial assembly models more complex than any before attempted by automated assembly planning systems, some having over 100 parts. A complete path from a CAD model to an automatically generated robot program for assembling the device represented by the CAD model has also been demonstrated

Task planning with uncertainty for robotic systems

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Industry 4.0 for SMEs

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies