Model-Based Coordination of Autonomous Vehicle Teams

2005 ◽  
Author(s):  
Cary Czichon ◽  
Robert W. Peterson ◽  
Erik Mettala ◽  
Jerry Speer ◽  
Jeff Stahl
Keyword(s):  
Autonomous Vehicle ◽  
Process Models ◽  
Behavior Modeling ◽  
Colored Petri Nets ◽  
Model Composition ◽  
Task List ◽  
Modeling Methodology ◽  
Multi Stage ◽  
Execution Environment ◽  
Robotic Vehicle

In order to coordinate autonomous robotic vehicle teams as they perform tactical tasks, a task formalism incorporating graphical (but mathematically rigorous) process models is being used. This extendable formalism, associated modeling methodology, and integrated modeling and execution environment are being developed by a U.S. Army funded SBIR project (RDECOM Contract N61339-04-C-0005). Colored Petri Nets (CPNs) provide the mathematical rigor needed for task and composite (ensemble) behavior modeling, while being conceptually elegant and easily displayed. Higher level task models can contain more fundamental models, allowing hierarchical model composition. Typed places within CPNs can hold tokens representing robotic equipment performing specific roles in a mission comprised of one or more tactical tasks. Army Tactical Tasks (ARTs) are defined within the Army Universal Task List (AUTL), FM 7-15. CPN mechanics support task synchronization and process simulation. CPN-based models can be enhanced to incorporate adaptive reasoning and dynamic/summative evaluation capabilities. In this SBIR project, executable task models are encapsulated by task agents operating within agent clusters. These clusters control virtual robotic vehicles (existing within constructive simulators like OneSAF) while multi-stage tactical missions are being performed.

The Formal Design Models of a Set of Abstract Data Types (ADTs)

2012 ◽  
pp. 288-315
Author(s):  
Yingxu Wang ◽  
Xinming Tan ◽  
Cyprian F. Ngolah ◽  
Philip Sheu
Keyword(s):  
Real Time ◽  
Cognitive Learning ◽  
Process Models ◽  
Behavioral Models ◽  
Abstract Data Types ◽  
Data Types ◽  
Dynamic Behaviors ◽  
Modeling Methodology ◽  
Abstract Data ◽  
Data Objects

Type theories are fundamental for underpinning data object modeling and system architectural design in computing and software engineering. Abstract Data Types (ADTs) are a set of highly generic and rigorously modeled data structures in type theory. ADTs also play a key role in Object-Oriented (OO) technologies for software system design and implementation. This paper presents a formal modeling methodology for ADTs using the Real-Time Process Algebra (RTPA), which allows both architectural and behavioral models of ADTs and complex data objects. Formal architectures, static behaviors, and dynamic behaviors of a set of ADTs are comparatively studied. The architectural models of the ADTs are created using RTPA architectural modeling methodologies known as the Unified Data Models (UDMs). The static behaviors of the ADTs are specified and refined by a set of Unified Process Models (UPMs) of RTPA. The dynamic behaviors of the ADTs are modeled by process dispatching technologies of RTPA. This work has been applied in a number of real-time and non-real-time system designs such as a Real-Time Operating System (RTOS+), a Cognitive Learning Engine (CLE), and the automatic code generator based on RTPA.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

Subsurface Deformation in Surface Mechanical Attrition Processes

2015 ◽  
Author(s):  
Zhiyu Wang ◽  
Saurabh Basu ◽  
Christopher Saldana
Keyword(s):  
Strain Hardening ◽  
Model Material ◽  
Process Models ◽  
Image Correlation ◽  
Analytical Models ◽  
Subsurface Deformation ◽  
Multi Stage ◽  
Mechanical Attrition ◽  
Dead Metal Zone ◽  
Plane Strain Deformation

A modified expanding cavity model (M-ECM) is developed to describe subsurface deformation for strain-hardening materials loaded in unit deformation configurations occurring in surface mechanical attrition. The predictive results of this model are validated by comparison with unit deformation experiments in a model material, oxygen free high conductivity copper, using a custom designed plane strain deformation setup. Subsurface displacement and strain fields are characterized using in-situ digital image correlation. It is shown that conventional analytical models used to describe plastic response in strain-hardening metals are not able to predict important characteristics of the morphology of the plastic zone, including evolution of the dead metal zone (DMZ), especially at large plastic depths. The M-ECM developed in the present study provides an accurate prediction of the strain distribution obtained in experiment and is of utility as a component in multi-stage process models of the final surface state in surface mechanical attrition.

Autonomous Robotic Vehicle (Robicle) With Ambient Intelligence

2009 ◽  
Author(s):  
Young-Jae Ryoo ◽  
Young-Hak Chang ◽  
Dae-Yeong Lim ◽  
Yong-Jun Lee
Keyword(s):  
Ambient Intelligence ◽  
Autonomous Vehicle ◽  
Magnetic Sensors ◽  
Sensor Output ◽  
Test Results ◽  
Position Measurement ◽  
Linear Region ◽  
Position Sensing ◽  
Magnetic Guidance ◽  
Robotic Vehicle

Magnetic sensing is a reliable technology that has been developed for the purposed of position measurement and guidance, especially for applications in autonomous robotic vehicles. To calculate a position of a magnetic guidance road, it should be estimated in real-time. While the capability of a microprocessor and memory spaces have the limitation in implementation. To solve the above problems, this paper proposes a new structure of the magnetic sensors included a vertical magnetic field. The proposed method uses the linear region of the sensor output, and position determination using a simple equation with a microcontroller. The position sensing technique was implemented in the guidance of autonomous vehicle. The test results show that position sensing can be useful for an autonomous robotic vehicle.

Study on the Design of Particle Removal System for Autonomous Robotic Vehicle

2013 ◽  
Vol 694-697 ◽  
pp. 1646-1651
Author(s):  
Bagus Bhirawa Putra ◽  
He Xu ◽  
Liu Zhao Jie
Keyword(s):  
Embedded System ◽  
Design Methodology ◽  
Wide Spectrum ◽  
Autonomous Vehicle ◽  
Particle Removal ◽  
Future Developments ◽  
Jet Nozzle ◽  
The Embedded System ◽  
Robotic Vehicle ◽  
Removal System

The robustness of an autonomous robotic vehicle (ARV) and the embedded supporting architecture permit the investigation of a wide spectrum of research options for particle removal and cleaning apparatus. Applications for particle removal are aimed at supporting the autonomous vehicle in performing its mission, especially in areas considered hazardous, hence emphasize the importance of the embedded system in which the development of air and water jet nozzle is being introduced. By understanding the present basic theory and design methodology, this would capture the outline for future developments of the novelty in particle removal methods especially in an autonomous robotic vehicle (ARV). Accordingly, it can be ascertained that at the same time the main line of the research on particle removal methods remains clear, still in a correspondence research context it is relatively easy to identify alternative subjects which are worthwhile to investigate further.

scholarly journals A new look at multi-stage models of cancer incidence

2018 ◽  
Author(s):  
Tyler Lian ◽  
Rick Durrett
Keyword(s):  
Branching Process ◽  
Probabilistic Approach ◽  
Process Models ◽  
Hyperbolic Partial Differential Equations ◽  
Main Method ◽  
Stage Models ◽  
Multi Stage ◽  
Cancer Initiation ◽  
Seer Data ◽  
The One

AbstractMulti-stage models have long been used in combination with SEER data to make inferences about the mechanisms underlying cancer initiation. The main method for studying these models mathematically has been the computation of generating functions by solving hyperbolic partial differential equations. Here, we analyze these models using a probabilistic approach similar to the one Durrett and Moseley [7] used to study branching process models of cancer. This more intuitive approach leads to simpler formulas and new insights into the behavior of these models. Unfortunately, the examples we consider suggest that fitting multi-stage models has very little power to make inferences about the number of stages unless parameters are constrained to take on realistic values.

Mathematical Institutional Economics and the Theory of Money and Financial Institutions

2016 ◽  
Author(s):  
Martin Shubik ◽  
Eric Smith
Keyword(s):  
Financial Institutions ◽  
Rational Expectations ◽  
Institutional Economics ◽  
Random Variable ◽  
Process Models ◽  
Modeling Methodology ◽  
Theory To Practice ◽  
The One ◽  
Simultaneous Move

Chapter 11 raises the question of what is meant by our usage of “theory”. Different disciplines utilize the word theory differently. Furthermore model and theory appear on occasion to be used interchangeably. Aristotle contrasted theory to practice. Praxis is the Greek term for doing. Mathematical theory is deductive. The sensory or empirical content is implicit in the axioms. The logical consequences of the axioms provide theorems. A semantic view stresses the connection between the axioms and the abstraction of some aspect of reality. We stress that the natural preliminary step before dynamics is to construct process models based on general equilibrium. This can be done utilizing single simultaneous move games. This is sufficient to show the critical roles of money and financial institutions without even having to discuss complication in information and behaviour. The evolution of money and many financial institutions does not even call for the presence of exogenous uncertainty. A single random variable is sufficient to illustrate innovation. We develop a general modeling methodology leading to the construction of models as playable games. Staying with the one move structure leads to describing a manageable number of minimal institutions (below 100). When we consider more moves and information the number of logically feasible and plausible institutions becomes hyperastronomical and we are forced into considering not merely structure but many variants of behaviour even within the simple scope of rational expectations. This problem is taken up in Chapter 12.

scholarly journals Systematic and Model-Assisted Process Design for the Extraction and Purification of Artemisinin from Artemisia annua L.—Part II: Model-Based Design of Agitated and Packed Columns for Multistage Extraction and Scrubbing

Processes ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 179 ◽  
Author(s):  
Axel Schmidt ◽  
Maximilian Sixt ◽  
Maximilian Huter ◽  
Fabian Mestmäcker ◽  
Jochen Strube
Keyword(s):  
Manufacturing Process ◽  
Process Model ◽  
Artemisia Annua ◽  
Scale Up ◽  
Plug Flow ◽  
Process Models ◽  
Extraction Column ◽  
Model Parameters ◽  
Multi Stage ◽  
Extraction And Purification

Liquid-liquid extraction (LLE) is an established unit operation in the manufacturing process of many products. However, development and integration of multistage LLE for new products and separation routes is often hindered and is probably more cost intensive due to a lack of robust development strategies and reliable process models. Even today, extraction columns are designed based on pilot plant experiments. For dimensioning, knowledge of phase equilibrium, hydrodynamics and mass transport kinetics are necessary. Usually, those must be determined experimentally for scale-up, at least in scales of DN50-150 (nominal diameter). This experiment-based methodology is time consuming and it requires large amounts of feedstock, especially in the early phase of the project. In this study the development for the integration of LLE in a new manufacturing process for artemisinin as an anti-malaria drug is presented. For this, a combination of miniaturized laboratory and mini-plant experiments supported by mathematical modelling is used. System data on extraction and washing distributions were determined by means of shaking tests and implemented as a multi-stage extraction in a process model. After the determination of model parameters for mass transfer and plant hydrodynamics in a droplet measurement apparatus, a distributed plug-flow model is used for scale-up studies. Operating points are validated in a mini-plant system. The mini-plant runs are executed in a Kühni-column (DN26) for extraction and a packed extraction column (DN26) for the separation of side components with a throughput of up to 3.6 L/h, yield of up to 100%, and purity of 41% in the feed mixture to 91% after washing.

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