Real-Time Kinematics Coordinated Swarm Robotics for Construction 3D Printing
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AI, Robots, and Swarms: Issues, Questions, and Recommended Studies
AI, Robots, and Swarms Issues, Questions, and Recommended Studies Andrew Ilachinski January 2017 Approved for Public Release; Distribution Unlimited. This document contains the best opinion of CNA at the time of issue. It does not necessarily represent the opinion of the sponsor. Distribution Approved for Public Release; Distribution Unlimited. Specific authority: N00014-11-D-0323. Copies of this document can be obtained through the Defense Technical Information Center at www.dtic.mil or contact CNA Document Control and Distribution Section at 703-824-2123. Photography Credits: http://www.darpa.mil/DDM_Gallery/Small_Gremlins_Web.jpg; http://4810-presscdn-0-38.pagely.netdna-cdn.com/wp-content/uploads/2015/01/ Robotics.jpg; http://i.kinja-img.com/gawker-edia/image/upload/18kxb5jw3e01ujpg.jpg Approved by: January 2017 Dr. David A. Broyles Special Activities and Innovation Operations Evaluation Group Copyright © 2017 CNA Abstract The military is on the cusp of a major technological revolution, in which warfare is conducted by unmanned and increasingly autonomous weapon systems. However, unlike the last “sea change,” during the Cold War, when advanced technologies were developed primarily by the Department of Defense (DoD), the key technology enablers today are being developed mostly in the commercial world. This study looks at the state-of-the-art of AI, machine-learning, and robot technologies, and their potential future military implications for autonomous (and semi-autonomous) weapon systems. While no one can predict how AI will evolve or predict its impact on the development of military autonomous systems, it is possible to anticipate many of the conceptual, technical, and operational challenges that DoD will face as it increasingly turns to AI-based technologies. -
Supporting Mobile Swarm Robotics in Low Power and Lossy Sensor Networks 1 Introduction
1 Supporting Mobile Swarm Robotics in Low Power and Lossy Sensor Networks Kevin Andrea [email protected] Robert Simon [email protected] Sean Luke [email protected] Department of Computer Science George Mason University 4400 University Drive MSN 4A5 Fairfax, VA 22030 USA Summary Wireless low-power and lossy networks (LLNs) are a key enabling technology for the deployment of massively scaled self-organizing sensor swarm systems. Supporting applications such as providing human users situational awareness across large areas requires that swarm-friendly LLNs effectively support communication between embedded and mobile devices, such as autonomous robots. The reason for this is that large scale embedded sensor applications such as unattended ground sensing systems typically do not have full end-to-end connectivity, but suffer frequent communication partitions. Further, it is desirable for many tactical applications to offload tasks to mobile robots. Despite the importance of support this communication pattern, there has been relatively little work in designing and evaluating LLN-friendly protocols capable of supporting such interactions. This paper addresses the above problem by describing the design, implementation, and evaluation of the MoRoMi system. MoRoMi stands for Mobile Robotic MultI-sink. It is intended to support autonomous mobile robots that interact with embedded sensor swarms engaged in activities such as cooperative target observation, collective map building, and ant foraging. These activities benefit if the swarm can dynamically interact with embedded sensing and actuator systems that provide both local environmental or positional information and an ad-hoc communication system. Our paper quantifies the performance levels that can be expected using current swarm and LLN technologies. -
Interactive Robots in Experimental Biology 3 4 5 6 Jens Krause1,2, Alan F.T
1 2 Interactive Robots in Experimental Biology 3 4 5 6 Jens Krause1,2, Alan F.T. Winfield3 & Jean-Louis Deneubourg4 7 8 9 10 11 12 1Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Department of Biology and 13 Ecology of Fishes, 12587 Berlin, Germany; 14 2Humboldt-University of Berlin, Department for Crop and Animal Sciences, Philippstrasse 15 13, 10115 Berlin, Germany; 16 3Bristol Robotics Laboratory, University of the West of England, Coldharbour Lane, Bristol 17 BS16 1QY, UK; 18 4Unit of Social Ecology, Campus Plaine - CP 231, Université libre de Bruxelles, Bd du 19 Triomphe, B-1050 Brussels - Belgium 20 21 22 23 24 25 26 27 28 Corresponding author: Krause, J. ([email protected]), Leibniz Institute of Freshwater 29 Ecology and Inland Fisheries, Department of the Biology and Ecology of Fishes, 30 Müggelseedamm 310, 12587 Berlin, Germany. 31 32 33 1 33 Interactive robots have the potential to revolutionise the study of social behaviour because 34 they provide a number of methodological advances. In interactions with live animals the 35 behaviour of robots can be standardised, morphology and behaviour can be decoupled (so that 36 different morphologies and behavioural strategies can be combined), behaviour can be 37 manipulated in complex interaction sequences and models of behaviour can be embodied by 38 the robot and thereby be tested. Furthermore, robots can be used as demonstrators in 39 experiments on social learning. The opportunities that robots create for new experimental 40 approaches have far-reaching consequences for research in fields such as mate choice, 41 cooperation, social learning, personality studies and collective behaviour. -
Carbon Nanotubes and Graphene As Additives in 3D Printing Lara A
University of Massachusetts Amherst ScholarWorks@UMass Amherst Chemistry Department Faculty Publication Series Chemistry 2016 Carbon Nanotubes and Graphene as Additives in 3D Printing Lara A. Al-Hariri University of Massachusetts Amherst Branden Leonhardt Florida State University Mesopotamia Nowotarski Florida State University James Magi Florida State University Kaelynn Chambliss Florida State University See next page for additional authors Follow this and additional works at: https://scholarworks.umass.edu/chem_faculty_pubs Part of the Chemistry Commons, and the Education Commons Recommended Citation Al-Hariri, Lara A.; Leonhardt, Branden; Nowotarski, Mesopotamia; Magi, James; Chambliss, Kaelynn; Venzel, Thaís; Delekar, Sagar; and Acquah, Steve, "Carbon Nanotubes and Graphene as Additives in 3D Printing" (2016). Carbon Nanotubes - Current Progress of their Polymer Composites. 1448. https://doi.org/10.5772/63419 This Article is brought to you for free and open access by the Chemistry at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Chemistry Department Faculty Publication Series by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. Authors Lara A. Al-Hariri, Branden Leonhardt, Mesopotamia Nowotarski, James Magi, Kaelynn Chambliss, Thaís Venzel, Sagar Delekar, and Steve Acquah This article is available at ScholarWorks@UMass Amherst: https://scholarworks.umass.edu/chem_faculty_pubs/1448 PUBLISHED BY World's largest Science, Technology & Medicine -
3D Printing Technology Applications in Occupational Therapy
Open Access Physical Medicine and Rehabilitation - International Special Article – Occupational Therapy 3D Printing Technology Applications in Occupational Therapy Ganesan B1,2, Al-Jumaily A1 and Luximon A2* 1Faculty of Engineering and IT, University of Technology Abstract Sydney, Australia With the rapid development of three dimensional technologies in last three 2The Hong Kong Polytechnic University, Hong Kong decades, it is widely spread worldwide and made dramatic impact into various *Corresponding author: Luximon Ameersing, The fields such as medicine, dentistry, other health care and engineering area. The Hong Kong Polytechnic University, Hung Hom, Hong promising future of this 3D printing technology made new future in the medicine Kong to design the various hard tissues, models of body parts, implants, orthosis and prosthesis with high accuracy. This paper focuses on the possibilities Received: May 26, 2016; Accepted: June 06, 2016; and benefits of 3D printing technology in the occupational therapy research Published: June 09, 2016 or clinical practice and presents the different procedures for creating different types of three dimensional physical models. Keywords: 3D printing; Occupational Therapy; Three dimensional Printing; Assistive devices Introduction 3D three-dimensional printing (3DP), Ink Jet printing techniques, vacuum casting and milling (VCM), two-photon polymerization Three dimensional (3D) printing is a novel emerging technology (TPP), direct laser metal sintering (DLMS) [6, 14]. In medicine, there widely used for various fields such as medical, engineering, are different types of materials are used to create rapid prototype educations, and other industrial areas. It is the process of making model of medical devices and implants such as stainless steel, Cobalt three dimensional physical models by using 3D software, computer, Chromium alloys (Co Cr), titanium (Ti) alloys, Polycaprolactone and printer. -
Challenges in the Optimization of 3D Printing of Zirconia Based Pastes By
Challenges in the optimization of 3D printing and robocasting processes using zirconia based pastes 2018 NanoMatLab/Biomat Meeting Robocasting - Introduction • Layer-by-layer deposition of ceramic slurries (paste) through a nozzle (extrusion). • Computer numerical control over nozzle position coordinates and piston movement. • Nozzle diameter ranging from 0.03mm to 2mm. Freeforming 24h. Ceramic parts with bespoke, intricate geometries can be produced quickly and inexpensively. Picture source: [1] Substrate bed heated to 30 [1], [2], [3] Robocasting – Products [4] [1] Robocasting - Slurries • Slurries must be pseudoplastic to flow through the nozzle. • Slurry compositions are kept close to the dilatant ratio. Dilatant Capillarity Adapted from [4] [2] Adapted from [2] • Dilatant mass maintains structural integrity after minimal drying time. • Heated bed speeds up the pseudoplastic to dilatant transition. [2], [4] Robocasting - Slurries • Slurries of high solid fraction, usually 50-65 vol.% ceramic powder. • 35-50 vol.% volatile solvent (usually water). • Higher ceramic loadings decrease sintering shrinkage and cracking. • Highly loaded slurries are prone to agglomeration, that can cause nozzle clogging during extrusion. • Tested slurries: Slurry designation Zirconia powder Powder/dispersant loading weight ratio X High High Y Medium Low Z Low Low [2], [3] 3D Printer Commercial open source 3D printer “Lulzbot MINI” Syringe Hypodermic (extruder) + needle (nozzle) Printing parameters Optimization - Example Movement Extruded slurry Increase flow -
Special Feature on Advanced Mobile Robotics
applied sciences Editorial Special Feature on Advanced Mobile Robotics DaeEun Kim School of Electrical and Electronic Engineering, Yonsei University, Shinchon, Seoul 03722, Korea; [email protected] Received: 29 October 2019; Accepted: 31 October 2019; Published: 4 November 2019 1. Introduction Mobile robots and their applications are involved with many research fields including electrical engineering, mechanical engineering, computer science, artificial intelligence and cognitive science. Mobile robots are widely used for transportation, surveillance, inspection, interaction with human, medical system and entertainment. This Special Issue handles recent development of mobile robots and their research, and it will help find or enhance the principle of robotics and practical applications in real world. The Special Issue is intended to be a collection of multidisciplinary work in the field of mobile robotics. Various approaches and integrative contributions are introduced through this Special Issue. Motion control of mobile robots, aerial robots/vehicles, robot navigation, localization and mapping, robot vision and 3D sensing, networked robots, swarm robotics, biologically-inspired robotics, learning and adaptation in robotics, human-robot interaction and control systems for industrial robots are covered. 2. Advanced Mobile Robotics This Special Issue includes a variety of research fields related to mobile robotics. Initially, multi-agent robots or multi-robots are introduced. It covers cooperation of multi-agent robots or formation control. Trajectory planning methods and applications are listed. Robot navigations have been studied as classical robot application. Autonomous navigation examples are demonstrated. Then services robots are introduced as human-robot interaction. Furthermore, unmanned aerial vehicles (UAVs) or autonomous underwater vehicles (AUVs) are shown for autonomous navigation or map building. -
Swarm Robotics”
applied sciences Editorial Editorial: Special Issue “Swarm Robotics” Giandomenico Spezzano Institute for High Performance Computing and Networking (ICAR), National Research Council of Italy (CNR), Via Pietro Bucci, 8-9C, 87036 Rende (CS), Italy; [email protected] Received: 1 April 2019; Accepted: 2 April 2019; Published: 9 April 2019 Swarm robotics is the study of how to coordinate large groups of relatively simple robots through the use of local rules so that a desired collective behavior emerges from their interaction. The group behavior emerging in the swarms takes its inspiration from societies of insects that can perform tasks that are beyond the capabilities of the individuals. The swarm robotics inspired from nature is a combination of swarm intelligence and robotics [1], which shows a great potential in several aspects. The activities of social insects are often based on a self-organizing process that relies on the combination of the following four basic rules: Positive feedback, negative feedback, randomness, and multiple interactions [2,3]. Collectively working robot teams can solve a problem more efficiently than a single robot while also providing robustness and flexibility to the group. The swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. In the model, the robots in the swarm should have some basic functions, such as sensing, communicating, motioning, and satisfy the following properties: 1. Autonomy—individuals that create the swarm-robotic system are autonomous robots. They are independent and can interact with each other and the environment. 2. Large number—they are in large number so they can cooperate with each other. -
Building 3D-Structures with an Intelligent Robot Swarm
BUILDING 3D-STRUCTURES WITH AN INTELLIGENT ROBOT SWARM A Dissertation Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Master of Science by Yiwen Hua May 2018 c 2018 Yiwen Hua ALL RIGHTS RESERVED BUILDING 3D-STRUCTURES WITH AN INTELLIGENT ROBOT SWARM Yiwen Hua, M.S. Cornell University 2018 This research is an extension to the TERMES system, a decentralized au- tonomous construction team composed of swarm robots building 2.5D struc- tures1, with custom-designed bricks. The work in this thesis concerns 1) im- proved mechanical design of the robots, 2) addition of heterogeneous building material, and 3) an extended algorithmic framework to use this material. In or- der to lower system cost and maintenance, the TERMES robot is redesigned for manufacturing in low-end 3D printers and the new drive train, including motor adapters and pulleys, is based on 3D printed components instead of machined aluminum. The work further extends the original system by enabling construc- tion of 3D structures without added hardware complexity in the robots. To do this, we introduce a reusable, spring-loaded expandable brick which can be eas- ily manufactured through one-step casting and which complies with the origi- nal robots and bricks. This thesis also introduces a decentralized construction algorithm that permits an arbitrary number of robots to build overhangs over convex cavities. To enable timely completion of large-scale structures, we also introduce a method by which to optimize the transition probabilities used by the robots to traverse the structure. -
A Study on 3D Printing and Its Effects on the Future of Transportation
CAIT-UTC-NC19 A Study on 3D Printing and its Effects on the Future of Transportation September 2018 Submitted by: Omar Jumaah, Doctoral Candidate Department of Mechanical and Aerospace Engineering Rutgers, The State University of New Jersey 98 Brett Road Piscataway, NJ 08854-8058 [email protected] External Project Manager Patrick Szary, PhD Associate Director, CAIT Central Administration Rutgers, The State University of New Jersey 100 Brett Road Piscataway, NJ 08854-8058 [email protected] In cooperation with Rutgers, The State University of New Jersey & State of Department of Transportation & U.S. Department of Transportation Federal Highway Administration i Disclaimer Statement The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation, University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof. The Center for Advanced Infrastructure and Transportation (CAIT) is a National UTC Consortium led by Rutgers, The State University. Members of the consortium are the University of Delaware, Utah State University, Columbia University, New Jersey Institute of Technology, Princeton University, University of Texas at El Paso, Virginia Polytechnic Institute, and University of South Florida. The Center is funded by the U.S. Department of Transportation. ii CAIT-UTC-NC19 1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No. CAIT-UTC-NC19 4. Title and Subtitle 5. Report Date A Study on 3D Printing and its Effects on the Future of Transportation September 2018 6. -
Special Issue on Distributed Robotics - from Fundamentals to Applications
This is a repository copy of Guest editorial: Special issue on distributed robotics - from fundamentals to applications. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/139581/ Version: Accepted Version Article: Gross, R. orcid.org/0000-0003-1826-1375, Kolling, A., Berman, S. et al. (3 more authors) (2018) Guest editorial: Special issue on distributed robotics - from fundamentals to applications. Autonomous Robots, 42 (8). pp. 1521-1523. ISSN 0929-5593 https://doi.org/10.1007/s10514-018-9803-9 The final publication is available at Springer via https://doi.org/10.1007/s10514-018-9803-9 Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Guest editorial: Special issue on distributed robotics - from fundamentals to applications Roderich Groß ([email protected]), The University of Sheffield, UK Andreas Kolling ([email protected]), iRobot, USA Spring Berman, ([email protected]), Arizona State University, USA Alcherio Martinoli ([email protected]), EPFL, Switzerland Emilio Frazzoli, ([email protected]), ETH Zürich, Switzerland Fumitoshi Matsuno ([email protected]), Kyoto University, Japan Distributed robotics is an interdisciplinary and rapidly growing area, combining research in computer science, communication and control systems, and electrical and mechanical engineering. -
3D-Printed Photoactive Semiconducting Nanowire
Forum Article Cite This: ACS Appl. Nano Mater. 2020, 3, 969−976 www.acsanm.org 3D-Printed Photoactive Semiconducting Nanowire−Polymer Composites for Light Sensors † † † ‡ § ∥ Xin Shan, Pengsu Mao, Haoran Li, Thomas Geske, Divya Bahadur, Yan Xin, § † ‡ Subramanian Ramakrishnan, and Zhibin Yu*, , † Department of Industrial and Manufacturing Engineering, High-Performance Materials Institute, FAMU-FSU College of ‡ § Engineering, Materials Science and Engineering, Department of Chemical and Biomedical Engineering, FAMU-FSU College of ∥ Engineering, and National High Magnetic Field Laboratory, Florida State University, Tallahassee, Florida 32310, United States *S Supporting Information ABSTRACT: We demonstrated 3D-printed photoactive composites for light sensors. The composites consist of semiconducting polymer nanowires dispersed in an insulating polymer matrix through a thermo- or photocuring process. The nanowires formed percolated networks for charge-carrier collection at a very low nanowire volume concentration. Photodetectors had been fabricated with such composites and obtained a low leakage current density of 25 nA cm−2, a large conductivity change of 18025 times upon light irradiation (1 sun), and a high specific detectivity of 4.5 × 1010 Jones. The composite precursors before curing had been used as paints on different surfaces including wood, cardboard, and glass fiber cloth to create photoactive coatings on these surfaces. The precursors had also been used for 3D printing to create photoactive structures with a mechanical modulus of 4 GPa and an ultimate strength of 36 MPa. KEYWORDS: 3D printing, composite, semiconductor, photodetector, P3HT, nanowire ■ INTRODUCTION certain desired spectra of electromagnetic radiation, which is difficult to achieve if metallic or insulating composites are Polymer-based composites have been widely used as structural 14 components in the automotive, construction, and aerospace used.