Dynamical Behavior of Multi-Robot Systems Using Lattice Gas Automata

Recent attention has been given to the deployment of an adaptable sensor array realized by multi-robotic systems. Our group has been studying the collective behavior of autonomous, multi-agent systems and their applications in the area of remote-sensing and emerging threats. To accomplish such tasks, an interdisciplinary research effort at Sandia National Laboratories are conducting tests in the fields of sensor technology, robotics, and multi-robotic and multi-agents architectures. Our goal is to coordinate a constellation of point sensors that optimizes spatial coverage and multivariate signal analysis using unmanned robotic vehicles (e.g., RATLERs, Robotic All-ten-sin Lunar Exploration Rover-class vehicles). Overall design methodology is to evolve complex collective behaviors realized through simple interaction (kinetic) physics and artificial intelligence to enable real-time operational responses to emerging threats. This paper focuses on our recent work understanding the dynamics of many-body systems using the physics-based hydrodynamic model of lattice gas automata. Three design features are investigated. One, for single-speed robots, a hexagonal nearest-neighbor interaction topology is necessary to preserve standard hydrodynamic flow. Two, adaptability, defined by the swarm's deformation rate, can be controlled through the hydrodynamic viscosity term, which, in turn, is defined by the local robotic interaction rules. Three, due to the inherent non-linearity of the dynamical equations describing large ensembles, development of stability criteria ensuring convergence to equilibrium states is developed by scaling information flow rates relative to a swarm's hydrodynamic flow rate. An initial test case simulates a swarm of twenty-five robots that maneuvers past an obstacle while following a moving target. A genetic algorithm optimizes applied nearest-neighbor forces in each of five spatial regions distributed over the simulation domain. Armed with knowledge, the swarm adapts by changing state in order to avoid the obstacle. Simulation results are qualitatively similar to lattice gas

Background, Systematic Review, Challenges and Outlook

Publisher Copyright: © 2013 IEEE. This research is supported by the Digital Manufacturing and Design Training Network (DiManD) project funded by the European Union through the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2018) under grant agreement no. 814078The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition.publishersversionpublishe

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Workshop on "Robotic assembly of 3D MEMS".

Proceedings of a workshop proposed in IEEE IROS'2007.The increase of MEMS' functionalities often requires the integration of various technologies used for mechanical, optical and electronic subsystems in order to achieve a unique system. These different technologies have usually process incompatibilities and the whole microsystem can not be obtained monolithically and then requires microassembly steps. Microassembly of MEMS based on micrometric components is one of the most promising approaches to achieve high-performance MEMS. Moreover, microassembly also permits to develop suitable MEMS packaging as well as 3D components although microfabrication technologies are usually able to create 2D and "2.5D" components. The study of microassembly methods is consequently a high stake for MEMS technologies growth. Two approaches are currently developped for microassembly: self-assembly and robotic microassembly. In the first one, the assembly is highly parallel but the efficiency and the flexibility still stay low. The robotic approach has the potential to reach precise and reliable assembly with high flexibility. The proposed workshop focuses on this second approach and will take a bearing of the corresponding microrobotic issues. Beyond the microfabrication technologies, performing MEMS microassembly requires, micromanipulation strategies, microworld dynamics and attachment technologies. The design and the fabrication of the microrobot end-effectors as well as the assembled micro-parts require the use of microfabrication technologies. Moreover new micromanipulation strategies are necessary to handle and position micro-parts with sufficiently high accuracy during assembly. The dynamic behaviour of micrometric objects has also to be studied and controlled. Finally, after positioning the micro-part, attachment technologies are necessary

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

Smart Manufacturing

This book is a collection of 11 articles that are published in the corresponding Machines Special Issue “Smart Manufacturing”. It represents the quality, breadth and depth of the most updated study in smart manufacturing (SM); in particular, digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the Internet to expand system capabilities, (3) supporting data-driven decision-making activities at various domains and levels of businesses, or (4) reconfiguring systems to adapt to changes and uncertainties. System smartness can be evaluated by one or a combination of performance metrics such as degree of automation, cost-effectiveness, leanness, robustness, flexibility, adaptability, sustainability, and resilience. This book features, firstly, the concepts digital triad (DT-II) and Internet of digital triad things (IoDTT), proposed to deal with the complexity, dynamics, and scalability of complex systems simultaneously. This book also features a comprehensive survey of the applications of digital technologies in space instruments; a systematic literature search method is used to investigate the impact of product design and innovation on the development of space instruments. In addition, the survey provides important information and critical considerations for using cutting edge digital technologies in designing and manufacturing space instruments

Adaptive Robot Framework: Providing Versatility and Autonomy to Manufacturing Robots Through FSM, Skills and Agents

207 p.The main conclusions that can be extracted from an analysis of the current situation and future trends of the industry,in particular manufacturing plants, are the following: there is a growing need to provide customization of products, ahigh variation of production volumes and a downward trend in the availability of skilled operators due to the ageingof the population. Adapting to this new scenario is a challenge for companies, especially small and medium-sizedenterprises (SMEs) that are suffering first-hand how their specialization is turning against them.The objective of this work is to provide a tool that can serve as a basis to face these challenges in an effective way.Therefore the presented framework, thanks to its modular architecture, allows focusing on the different needs of eachparticular company and offers the possibility of scaling the system for future requirements. The presented platform isdivided into three layers, namely: interface with robot systems, the execution engine and the application developmentlayer.Taking advantage of the provided ecosystem by this framework, different modules have been developed in order toface the mentioned challenges of the industry. On the one hand, to address the need of product customization, theintegration of tools that increase the versatility of the cell are proposed. An example of such tools is skill basedprogramming. By applying this technique a process can be intuitively adapted to the variations or customizations thateach product requires. The use of skills favours the reuse and generalization of developed robot programs.Regarding the variation of the production volumes, a system which permits a greater mobility and a faster reconfigurationis necessary. If in a certain situation a line has a production peak, mechanisms for balancing the loadwith a reasonable cost are required. In this respect, the architecture allows an easy integration of different roboticsystems, actuators, sensors, etc. In addition, thanks to the developed calibration and set-up techniques, the system canbe adapted to new workspaces at an effective time/cost.With respect to the third mentioned topic, an agent-based monitoring system is proposed. This module opens up amultitude of possibilities for the integration of auxiliary modules of protection and security for collaboration andinteraction between people and robots, something that will be necessary in the not so distant future.For demonstrating the advantages and adaptability improvement of the developed framework, a series of real usecases have been presented. In each of them different problematic has been resolved using developed skills,demonstrating how are adapted easily to the different casuistic

Application of ”ART SIMULATOR” for Manufacturing Similarity Identification in Group Technology Design - Chapter 10

This chapter 10 carried out the exceptional implementation of ART-1 neural network in the analysis of the manufacturing similarity of the cylindrical parts within the group technology design. Established concept of the group technology design begins from the complex part of the group or the group representative. Group representative has all the geometrical elements of the parts in group, and manufacturing procedure may be applied to the machining of any part in the group. The complex part may be realistic or a hypothetical one. The ART-1 artificial neural network provided manufacturing classification according to the geometrical similarities of work-pieces for the group of cylindrical parts. For the manufacturing similarity identification within the group technology design, software package "ART Simulator" is developed and presented in this chapter