An approach to task coordination for hyperflexible robotic workcells

2014 - 2015The manufacturing industry is very diverse and covers a wide range of specific processes ranging from extracting minerals to assembly of very complex products such as planes or computers, with all intermediate processing steps in a long chain of industrial suppliers and customers. It is well know that the introduction of robots in manufacturing industries has many advantages. Basically, in relation to human labor, robots work to a constant level of quality. For example, waste, scrap and rework are minimized. Furthermore they can work in areas that are hazardous or unpleasant to humans. Robots are advantageous where strength is required, and in many applications they are also faster than humans. Also, in relation to special-purpose dedicated equipment, robots are more easily reprogrammed to cope with new products or changes in the design of existing ones. In the last 30-40 years, large enterprises in high-volume markets have managed to remain competitive and maintain qualified jobs by increasing their productivity with the incremental adoption and use of advanced ICT and robotics technologies. In the 70s, robots have been introduced for the automation of a wide spectrum of tasks such as: assembly of cars, white goods, electronic devices, machining of metal and plastic parts, and handling of workpieces and objects of all kinds. Robotics has thus soon become a synonym for competitive manufacturing and a key contributing technology for strengthening the economic base of Europe . So far, the automotive and electronics industries and their supply chains are the main users of robot systems and are accounting for more than 60% of the total annual robot sales. Robotic technologies have thus mainly been driven by the needs of these high-volume market industries. The degree of automation in the automotive industries is expected to increase in the future as robots will push the limits towards flexibility regarding faster change-over-times of different product types (through rapid programming generation schemes), capabilities to deal with tolerances (through an extensive use of sensors) and costs (by reducing customized work-cell installations and reuse of manufacturing equipment). There are numerous new fields of applications in which robot technology is not widespread today due to its lack of flexibility and high costs involved when dealing with varying lot sizes and variable product geometries. In such cases, hyper-flexible robotic work cells can help in providing flexibility to the system and making it adaptable to the different dynamic production requirements. Hyper-flexible robotic work cells, in fact, can be composed of sets of industrial robotic manipulators that cooperate to achieve the production step that characterize the work cell; they can be programmed and re-programmed to achieve a wide class of operations and they may result versatile to perform different kind of tasks Related key technology challenges for pursuing successful long-term industrial robot automation are introduced at three levels: basic technologies, robot components and systems integration. On a systems integration level, the main challenges lie in the development of methods and tools for instructing and synchronising the operation of a group of cooperative robots at the shop-floor. Furthermore, the development of the concept of hyper flexible manufacturing systems implies soon the availability of: consistent middleware for automation modules to seamlessly connect robots, peripheral devices and industrial IT systems without reprogramming everything (”plug-and-play”) . In this thesis both innovative and traditional industrial robot applications will be analyzed from the point of view of task coordination. In the modeling environment, contribution of this dissertation consists in presenting a new methodology to obtain a model oriented to the control the sequencing of the activities of a robotic hyperflexible cell. First a formal model using the Colored Modified Hybrid Petri Nets (CMHPN) is presented. An algorithm is provided to obtain an automatic synthesis of the CMHPN of a robotic cell with detail attention to aircraft industry. It is important to notice that the CMHPN is used to model the cell behaviour at a high level of abstraction. It models the activities of each cell component and its coordination by a supervisory system. As more, an object oriented approach and supervisory control are proposed to implement industrial automation control systems (based on Programmable Logic Controllers) to meet the new challenges of this field capability to implement applications involving widely distributed devices and high reuse of software components. Hence a method is proposed to implement both controllers and supervisors designed by Petri Nets on Programmable Logic Controllers (PLCs) using Object Oriented Programming (OOP). Finally preliminary results about a novel cyber-physical approach to the design of automated warehouse systems is presented. [edited by author]XIV n.s

Hierarchical robust supervisory control of discrete-event systems

The problem of Robust Supervisory Control (RSC) of Discrete-Event Systems (DES) is concerned with situations in which the DES plant model has dynamics uncertainty. A main challenge in the development of solutions for supervisory control problems (including RSC) is the issue of complexity of resulting solutions. Hierarchical approaches to supervision have been found to be effective in mitigating the above issue. In hierarchical control, a high-level supervisor designed based on a simplified high-level model of the plant, receives information about important events in the plant and issues high-level supervisory commands. In this thesis, the problem of hierarchical robust supervisory control under partial observation is studied. First, the setup of Zhong-Wonham for hierarchical control is extended to the case of control under partial observation. A Factorization property is derived that the reporting map must satisfy so that the reports sent to the high-level supervisor rely only on the low-level observable sequences. Furthermore, the three properties of Unobservable-and-Unique-Controllability (UUC), Unobservable-and-Uncontrollable-Prefixes-for-Observability (UUPO) and Partially-Observable-Strict-Output-Control-Consistency (PO-SOCC) are introduced and showed to ensure hierarchical consistency. Algorithms for modification of the plant model and reporting map (if necessary) to satisfy the Factorization, UUC, UUPO and PO-SOCC properties have also been developed. Next, the problem of robust supervisory control of a finite family of discrete-event plants is studied. Each plant has a separate closed specification language. A hierarchical solution is developed assuming full observation and then extended to the case of partial observation, following the approach in the thesis for hierarchical control under partial observation. Finally, a case study involving a flexible manufacturing system production line is studied where a machine is prone to failure. Following the approach developed in this thesis, a hierarchical robust supervisory control is designed to solve the control problem

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

Intelligent control of industrial processes

A detailed survey of the field of intelligent control is presented. Current practices are reviewed and the need for a unifying framework to identify and strengthen the underlying core principles is postulated. Intelligent control is redefined to make explicit use of human systems in control as a reference model. Psychological theories of intelligent behaviour reveal certain basic attributes. From these a set of necessary and sufficient conditions for intelligent control are derived. Learning ability is identified as a crucial element. Necessary attributes for learning are prediction capabilities, internal world model, estimation of the model parameters, and active probing to reduce uncertainties. This framewoik is used to define a Learning Based Predictive Control (LBPC) strategy. LBPC is derived from Predictive Functional Control techniques with an adaptive layer implemented by recursive least squares. Improved performance above conventional adaptive control is demonstrated. Distributed parameter systems are identified as a suitable application area requiring an intelligent control approach. Such systems are invariably complex, ill-defined, and nonlinear. Plasticating extrusion processes are considered in particular. LBPC is applied to control of the primary loop to regulate melt temperature and pressure at the die. A novel control technique is proposed for dynamic profile control of extruder barrel wall temperature. This is a two-level hierarchical scheme combining the benefits of LBPC control blocks at the lowest level with decision logic operating at the higher level as a supervisor. This Logic Based Strategy allows multivariable control of non-square systems with more outputs than inputs. The application of LBS to an extruder is demonstrated

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Graduate Catalog, 1996-1999, New Jersey Institute of Technology

https://digitalcommons.njit.edu/coursecatalogs/1003/thumbnail.jp