Robotics Course Guidebook
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Current Advances in Cognitive Robotics Amir Aly, Sascha Griffiths, Francesca Stramandinoli
Towards Intelligent Social Robots: Current Advances in Cognitive Robotics Amir Aly, Sascha Griffiths, Francesca Stramandinoli To cite this version: Amir Aly, Sascha Griffiths, Francesca Stramandinoli. Towards Intelligent Social Robots: Current Advances in Cognitive Robotics . France. 2015. hal-01673866 HAL Id: hal-01673866 https://hal.archives-ouvertes.fr/hal-01673866 Submitted on 1 Jan 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Proceedings of the Full Day Workshop Towards Intelligent Social Robots: Current Advances in Cognitive Robotics in Conjunction with Humanoids 2015 South Korea November 3, 2015 Amir Aly1, Sascha Griffiths2, Francesca Stramandinoli3 1- ENSTA ParisTech – France 2- Queen Mary University – England 3- Italian Institute of Technology – Italy Towards Emerging Multimodal Cognitive Representations from Neural Self-Organization German I. Parisi, Cornelius Weber and Stefan Wermter Knowledge Technology Institute, Department of Informatics University of Hamburg, Germany fparisi,weber,[email protected] http://www.informatik.uni-hamburg.de/WTM/ Abstract—The integration of multisensory information plays a processing of a huge amount of visual information to learn crucial role in autonomous robotics. In this work, we investigate inherent spatiotemporal dependencies in the data. To tackle how robust multimodal representations can naturally develop in this issue, learning-based mechanisms have been typically used a self-organized manner from co-occurring multisensory inputs. -
Impact of the Maker Movement
Impact of the maker movement Developed by Deloitte Center for the Edge and Maker Media from the Maker Impact Summit Dec. 2013 I AM A MAKER with my own two hands I forge the future from my imagining my work, my sweat with these tools i can build worlds here i put wire and foam transistor and plastic rubber metal and wood together to make something new what does it do where will this take us new places new worlds all from my workshop Malcolm S. Hoover, 2014 TABLE OF CONTENTS A Future of Potential 4 Overview 7 Letters from Conveners 10 How to Read This Document 14 How might the Maker Movement have an impact on… 15 • Manufacturing 16 • Education 19 • Government and Public Policy 22 • Citizen Science 25 • Retail 28 What Happens Next? 30 Participants 32 Other Images from the Summit 38 A FUTURE OF POTENTIAL We are on the cusp of an opportunity to more fully We are in a correction of sorts. Driven by the goal of scale tap into our creative potential, driven by significant efficiencies and low costs, the supply chain has been technological innovation that is democratizing the means stretched to the far extremes, like a bungee cord, and now of production and enabling connections between resources it’s starting to come back as the underlying economics and markets. Realizing this opportunity will require change. Where will we end up? We’ve learned in the last re-thinking and redesigning all of our major institutions, 15 years that experimentation is the key to innovation. -
A Humanoid Robot
NAIN 1.0 – A HUMANOID ROBOT by Shivam Shukla (1406831124) Shubham Kumar (1406831131) Shashank Bhardwaj (1406831117) Department of Electronics & Communication Engineering Meerut Institute of Engineering & Technology Meerut, U.P. (India)-250005 May, 2018 NAIN 1.0 – HUMANOID ROBOT by Shivam Shukla (1406831124) Shubham Kumar (1406831131) Shashank Bhardwaj (1406831117) Submitted to the Department of Electronics & Communication Engineering in partial fulfillment of the requirements for the degree of Bachelor of Technology in Electronics & Communication Meerut Institute of Engineering & Technology, Meerut Dr. A.P.J. Abdul Kalam Technical University, Lucknow May, 2018 DECLARATION I hereby declare that this submission is my own work and that, to the best of my knowledge and belief, it contains no material previously published or written by another person nor material which to a substantial extent has been accepted for the award of any other degree or diploma of the university or other institute of higher learning except where due acknowledgment has been made in the text. Signature Signature Name: Mr. Shivam Shukla Name: Mr. Shashank Bhardwaj Roll No. 1406831124 Roll No. 1406831117 Date: Date: Signature Name: Mr. Shubham Kumar Roll No. 1406831131 Date: ii CERTIFICATE This is to certify that Project Report entitled “Humanoid Robot” which is submitted by Shivam Shukla (1406831124), Shashank Bhardwaj (1406831117), Shubahm Kumar (1406831131) in partial fulfillment of the requirement for the award of degree B.Tech in Department of Electronics & Communication Engineering of Gautam Buddh Technical University (Formerly U.P. Technical University), is record of the candidate own work carried out by him under my/our supervision. The matter embodied in this thesis is original and has not been submitted for the award of any other degree. -
Remote and Autonomous Controlled Robotic Car Based on Arduino with Real Time Obstacle Detection and Avoidance
Universal Journal of Engineering Science 7(1): 1-7, 2019 http://www.hrpub.org DOI: 10.13189/ujes.2019.070101 Remote and Autonomous Controlled Robotic Car based on Arduino with Real Time Obstacle Detection and Avoidance Esra Yılmaz, Sibel T. Özyer* Department of Computer Engineering, Çankaya University, Turkey Copyright©2019 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Abstract In robotic car, real time obstacle detection electronic devices. The environment can be any physical and obstacle avoidance are significant issues. In this study, environment such as military areas, airports, factories, design and implementation of a robotic car have been hospitals, shopping malls, and electronic devices can be presented with regards to hardware, software and smartphones, robots, tablets, smart clocks. These devices communication environments with real time obstacle have a wide range of applications to control, protect, image detection and obstacle avoidance. Arduino platform, and identification in the industrial process. Today, there are android application and Bluetooth technology have been hundreds of types of sensors produced by the development used to implementation of the system. In this paper, robotic of technology such as heat, pressure, obstacle recognizer, car design and application with using sensor programming human detecting. Sensors were used for lighting purposes on a platform has been presented. This robotic device has in the past, but now they are used to make life easier. been developed with the interaction of Android-based Thanks to technology in the field of electronics, incredibly device. -
An Innovative Mechanical and Control Architecture for a Biomimetic Hexapod for Planetary Exploration M
An Innovative Mechanical and Control Architecture for a Biomimetic Hexapod for Planetary Exploration M. Pavone∗, P. Arenax and L. Patane´x ∗Scuola Superiore di Catania, Via S. Paolo 73, 95123 Catania, Italy xDipartimento di Ingegneria Elettrica Elettronica e dei Sistemi, Universita` degli Studi di Catania, Viale A. Doria, 6 - 95125 Catania, Italy Abstract— This paper addresses the design of a six locomotion are: wheels, caterpillar treads and legs. legged robot for planetary exploration. The robot is Wheeled and tracked robots are much easier to design specifically designed for uneven terrains and is bio- and to implement if compared with legged robots and logically inspired on different levels: mechanically as led to successful missions like Mars Pathfinder or well as in control. A novel structure is developed Spirit and Opportunity; nevertheless, they carry a set basing on a (careful) emulation of the cockroach, whose of disadvantages that hamper their use in more com- extraordinary agility and speed are principally due to its self-stabilizing posture and specializing legged plex explorative tasks. Firstly, wheeled and tracked function. Structure design enhances these properties, vehicles, even if designed specifically for harsh ter- in particular with an innovative piston-like scheme rains, cannot maneuver over an obstacle significantly for rear legs, while avoiding an excessive and useless shorter than the vehicle itself; a legged vehicle, on the complexity. Locomotion control is designed following an other hand, could be expected to climb an obstacle analog electronics approach, that in space applications up to twice its own height, much like a cockroach could hold many benefits. In particular, the locomotion can. -
Annual Report 2014 OUR VISION
AMOS Centre for Autonomous Marine Operations and Systems Annual Report 2014 Annual Report OUR VISION To establish a world-leading research centre for autonomous marine operations and systems: To nourish a lively scientific heart in which fundamental knowledge is created through multidisciplinary theoretical, numerical, and experimental research within the knowledge fields of hydrodynamics, structural mechanics, guidance, navigation, and control. Cutting-edge inter-disciplinary research will provide the necessary bridge to realise high levels of autonomy for ships and ocean structures, unmanned vehicles, and marine operations and to address the challenges associated with greener and safer maritime transport, monitoring and surveillance of the coast and oceans, offshore renewable energy, and oil and gas exploration and production in deep waters and Arctic waters. Editors: Annika Bremvåg and Thor I. Fossen Copyright AMOS, NTNU, 2014 www.ntnu.edu/amos AMOS • Annual Report 2014 Table of Contents Our Vision ........................................................................................................................................................................ 2 Director’s Report: Licence to Create............................................................................................................................. 4 Organization, Collaborators, and Facts and Figures 2014 ......................................................................................... 6 Presentation of New Affiliated Scientists................................................................................................................... -
AUV Adaptive Sampling Methods: a Review
applied sciences Review AUV Adaptive Sampling Methods: A Review Jimin Hwang 1 , Neil Bose 2 and Shuangshuang Fan 3,* 1 Australian Maritime College, University of Tasmania, Launceston 7250, TAS, Australia; [email protected] 2 Department of Ocean and Naval Architectural Engineering, Memorial University of Newfoundland, St. John’s, NL A1C 5S7, Canada; [email protected] 3 School of Marine Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China * Correspondence: [email protected] Received: 16 July 2019; Accepted: 29 July 2019; Published: 2 August 2019 Abstract: Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced. This paper presents an overview of existing adaptive sampling techniques. Included are adaptive mission uses and underlying methods for perception, interpretation and reaction to underwater phenomena in AUV operations. The potential for future research in adaptive missions is discussed. Keywords: autonomous underwater vehicle(s); maritime robotics; adaptive sampling; underwater feature tracking; in-situ sensors; sensor fusion 1. Introduction Autonomous underwater vehicles (AUVs) are unmanned marine robots. Owing to their mobility and increased ability to accommodate sensors, they have been used for a broad range of oceanographic missions, such as surveying underwater plumes and other phenomena, collecting bathymetric data and tracking oceanographic dynamic features. -
Development of the Crew Dragon ECLSS
ICES-2020-333 Development of the Crew Dragon ECLSS Jason Silverman1, Andrew Irby2, and Theodore Agerton3 Space Exploration Technologies, Hawthorne, California, 90250 SpaceX designed the Crew Dragon spacecraft to be the safest ever flown and to restore the ability of the United States to launch astronauts. One of the key systems required for human flight is the Environmental Control and Life Support System (ECLSS), which was designed to work in concert with the spacesuit and spacecraft. The tight coupling of many subsystems combined with an emphasis on simplicity and fault tolerance created unique challenges and opportunities for the design team. During the development of the crew ECLSS, the Dragon 1 cargo spacecraft flew with a simple ECLSS for animals, providing an opportunity for technology development and the early characterization of system-level behavior. As the ECLSS design matured a series of tests were conducted, including with humans in a prototype capsule in November 2016, the Demo-1 test flight to the ISS in March 2019, and human-in-the-loop ground testing in the Demo-2 capsule in January 2020 before the same vehicle performs a crewed test flight. This paper describes the design and operations of the ECLSS, the development process, and the lessons learned. Nomenclature AC = air conditioning AQM = air quality monitor AVV = active vent valve CCiCap = Commercial Crew Integrated Capability CCtCap = Commercial Crew Transportation Capability CFD = computational fluid dynamics conops = concept of operations COPV = composite overwrapped -
An Introduction to the NASA Robotics Alliance Cadets Program
Session F An Introduction to the NASA Robotics Alliance Cadets Program David R. Schneider, Clare van den Blink NASA, DAVANNE, & Cornell University / Cornell University CIT [email protected], [email protected] Abstract The 2006 report National Defense Education and Innovation Initiative highlighted this nation’s growing need to revitalize undergraduate STEM education. In response, NASA has partnered with the DAVANNE Corporation to create the NASA Robotics Alliance Cadets Program to develop innovative, highly integrated and interactive curriculum to redesign the first two years of Mechanical Engineering, Electrical Engineering and Computer Science. This paper introduces the NASA Cadets Program and provides insight into the skill areas targeted by the program as well as the assessment methodology for determining the program’s effectiveness. The paper also offers a brief discussion on the capabilities of the program’s robotic platform and a justification for its design into the program. As an example of the integration of the robotic platform with the program’s methodologies, this paper concludes by outlining one of the first educational experiments of NASA Cadets Program at Cornell University to be implemented in the Spring 2007 semester. I. Introduction To be an engineer is to be a designer, a creator of new technology, and the everyday hero that solves society’s problems through innovative methods and products by making ideas become a reality. However, the opportunity to truly explore these key concepts of being an engineer are often withheld from most incoming engineering students until at least their junior year causing many new students to lose motivation and potentially leave the program. -
Development of an Open Humanoid Robot Platform for Research and Autonomous Soccer Playing
Development of an Open Humanoid Robot Platform for Research and Autonomous Soccer Playing Karl J. Muecke and Dennis W. Hong RoMeLa: Robotics and Mechanisms Lab Virginia Tech Blacksburg, VA 24061 [email protected], [email protected] Abstract This paper describes the development of a fully autonomous humanoid robot for locomotion research and as the first US entry in to RoboCup. DARwIn (Dynamic Anthropomorphic Robot with Intelligence) is a humanoid robot capable of bipedal walking and performing human like motions. As the years have progressed, DARwIn has evolved from a concept to a sophisticated robot platform. DARwIn 0 was a feasibility study that investigated the possibility of making a humanoid robot walk. Its successor, DARwIn I, was a design study that investigated how to create a humanoid robot with human proportions, range of motion, and kinematic structure. DARwIn IIa built on the name ªhumanoidº by adding autonomy. DARwIn IIb improved on its predecessor by adding more powerful actuators and modular computing components. Finally, DARwIn III is designed to take the best of all the designs and incorporate the robot's most advanced motion control yet. Introduction Dynamic Anthropomorphic Robot with Intelligence (DARwIn), a humanoid robot, is a sophisticated hardware platform used for studying bipedal gaits that has evolved over time. Five versions of DARwIn have been developed, each an improvement on its predecessor. The first version, DARwIn 0 (Figure 1a), was used as a design study to determine the feasibility of creating a humanoid robot abd for actuator evaluation. The second version, DARwIn I (Figure 1b), used improved gaits and software. -
Hospitality Robots at Your Service WHITEPAPER
WHITEPAPER Hospitality Robots At Your Service TABLE OF CONTENTS THE SERVICE ROBOT MARKET EXAMPLES OF SERVICE ROBOTS IN THE HOSPITALITY SPACE IN DEPTH WITH SAVIOKE’S HOSPITALITY ROBOTS PEPPER PROVIDES FRIENDLY, FUN CUSTOMER ASSISTANCE SANBOT’S HOSPITALITY ROBOTS AIM FOR HOTELS, BANKING EXPECT MORE ROBOTS DOING SERVICE WORK roboticsbusinessreview.com 2 MOBILE AND HUMANOID ROBOTS INTERACT WITH CUSTOMERS ACROSS THE HOSPITALITY SPACE Improvements in mobility, autonomy and software drive growth in robots that can provide better service for customers and guests in the hospitality space By Ed O’Brien Across the business landscape, robots have entered many different industries, and the service market is no difference. With several applications in the hospitality, restaurant, and healthcare markets, new types of service robots are making life easier for customers and employees. For example, mobile robots can now make deliveries in a hotel, move materials in a hospital, provide security patrols on large campuses, take inventories or interact with retail customers. They offer expanded capabilities that can largely remove humans from having to perform repetitive, tedious, and often unwanted tasks. Companies designing and manufacturing such robots are offering unique approaches to customer service, providing systems to help fill in areas where labor shortages are prevalent, and creating increased revenues by offering new delivery channels, literally and figuratively. However, businesses looking to use these new robots need to be mindful of reviewing the underlying demand to ensure that such investments make sense in the long run. In this report, we will review the different types of robots aimed at providing hospitality services, their various missions, and expectations for growth in the near-to-immediate future. -
Psychological Aspect of Cognitive Robotics
VI Psychological Aspect of Cognitive Robotics 169 CHAPTER 9 Robotic Action Control: On the Crossroads of Cognitive Psychology and Cognitive Robotics Roy de Kleijn Leiden Institute for Brain and Cognition, Leiden University, The Netherlands. George Kachergis Leiden Institute for Brain and Cognition, Leiden University, The Netherlands. Bernhard Hommel Leiden Institute for Brain and Cognition, Leiden University, The Netherlands. CONTENTS 9.1 Early history of the fields .................................... 172 9.1.1 History of cognitive psychology .................... 172 9.1.2 The computer analogy ............................... 173 9.1.3 Early cognitive robots ................................ 174 9.2 Action control ................................................. 174 9.2.1 Introduction ........................................... 175 9.2.2 Feedforward and feedback control in humans ..... 175 9.2.3 Feedforward and feedback control in robots ....... 176 9.2.4 Robotic action planning .............................. 177 9.3 Acquisition of action control ................................. 178 9.3.1 Introduction ........................................... 178 9.3.2 Human action-effect learning ....................... 179 171 172 Cognitive Robotics 9.3.2.1 Traditional action-effect learning research .................................. 179 9.3.2.2 Motor babbling .......................... 179 9.3.3 Robotic action-effect learning ........................ 180 9.4 Directions for the future ...................................... 181 9.4.1 Introduction ..........................................