Remote and Autonomous Controlled Robotic Car Based on Arduino with Real Time Obstacle Detection and Avoidance
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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 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. -
Executive Summary World Robotics 2019 Service Robots 11
Executive Summary World Robotics 2019 Service Robots 11 Executive Summary World Robotics 2019 Service Robots Service robotics encompasses a broad field of applications, most of which having unique designs and different degrees of automation – from full tele-operation to fully autonomous operation. Hence, the industry is more diverse than the industrial robot industry (which is extensively treated in the companion publication World Robotics – Industrial Robots 2019). IFR Statistical Department is currently aware of more than 750 companies producing service robots or doing commercial research for marketable products. A full list is included in chapter 4 of World Robotics Service Robots 2019. IFR Statistical Department is continuously seeking for new service robot producers, so please contact [email protected] if you represent such a company and would like to participate in the annual survey conducted in the first quarter of each year. Participants receive the survey results free of charge. Sales of professional service robots on the rise The total number of professional service robots sold in 2018 rose by 61% to more than 271,000 units, up from roughly 168,000 in 2017. The sales value increased by 32% to USD 9.2 billion. Autonomous guided vehicles (AGVs) represent the largest fraction in the professional service robot market (41% of all units sold). They are established in non-manufacturing environments, mainly logistics, and have lots of potential in manufacturing. The second largest category (39% of all units sold), inspection and maintenance robots, covers a wide range of robots from rather low-priced standard units to expensive custom solutions. Service robots for defense applications accounted for 5% of the total number of service robots for professional use sold in 2018. -
How Humanoid Robots Influence Service Experiences and Food Consumption
Marketing Science Institute Working Paper Series 2017 Report No. 17-125 Service Robots Rising: How Humanoid Robots Influence Service Experiences and Food Consumption Martin Mende, Maura L. Scott, Jenny van Doorn, Ilana Shanks, and Dhruv Grewal “Service Robots Rising: How Humanoid Robots Influence Service Experiences and Food Consumption” © 2017 Martin Mende, Maura L. Scott, Jenny van Doorn, Ilana Shanks, and Dhruv Grewal; Report Summary © 2017 Marketing Science Institute MSI working papers are distributed for the benefit of MSI corporate and academic members means, electronic or mechanical, without written permission. Report Summary Interactions between consumers and humanoid service robots (i.e., robots with a human-like morphology such as a face, arms, and legs) soon will be part of routine marketplace experiences, and represent a primary arena for innovation in services and shopper marketing. At the same time, it is not clear whether humanoid robots, relative to human employees, trigger positive or negative consequences for consumers and companies. Although creating robots that appear as much like humans as possible is the “holy grail” in robotics, there is a risk that consumers will respond negatively to highly human-like robots, due to the feelings of discomfort that such robots can evoke. Here, Martin Mende, Maura Scott, Jenny van Doorn, Ilana Shanks, and Dhruv Grewal investigate whether humanoid service robots (HSRs) trigger discomfort and what the consequences might be for customers’ service experiences. They focus on the effects of HSRs in a food consumption context. Six experimental studies, conducted in the context of restaurant services, reveal that consumers report lower assessments of the server when their food is served by a humanoid service robot than by a human server, but their desire for food and their actual food consumption increases. -
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. -
Learning Preference Models for Autonomous Mobile Robots in Complex Domains
Learning Preference Models for Autonomous Mobile Robots in Complex Domains David Silver CMU-RI-TR-10-41 December 2010 Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania, 15213 Thesis Committee: Tony Stentz, chair Drew Bagnell David Wettergreen Larry Matthies Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Robotics Copyright c 2010. All rights reserved. Abstract Achieving robust and reliable autonomous operation even in complex unstruc- tured environments is a central goal of field robotics. As the environments and scenarios to which robots are applied have continued to grow in complexity, so has the challenge of properly defining preferences and tradeoffs between various actions and the terrains they result in traversing. These definitions and parame- ters encode the desired behavior of the robot; therefore their correctness is of the utmost importance. Current manual approaches to creating and adjusting these preference models and cost functions have proven to be incredibly tedious and time-consuming, while typically not producing optimal results except in the sim- plest of circumstances. This thesis presents the development and application of machine learning tech- niques that automate the construction and tuning of preference models within com- plex mobile robotic systems. Utilizing the framework of inverse optimal control, expert examples of robot behavior can be used to construct models that generalize demonstrated preferences and reproduce similar behavior. Novel learning from demonstration approaches are developed that offer the possibility of significantly reducing the amount of human interaction necessary to tune a system, while also improving its final performance. Techniques to account for the inevitability of noisy and imperfect demonstration are presented, along with additional methods for improving the efficiency of expert demonstration and feedback. -
Uncorrected Proof
JrnlID 10846_ ArtID 9025_Proof# 1 - 14/10/2005 Journal of Intelligent and Robotic Systems (2005) # Springer 2005 DOI: 10.1007/s10846-005-9025-1 Temporal Range Registration for Unmanned 1 j Ground and Aerial Vehicles 2 R. MADHAVAN*, T. HONG and E. MESSINA 3 Intelligent Systems Division, National Institute of Standards and Technology, Gaithersburg, MD 4 20899-8230, USA; e-mail: [email protected], {tsai.hong, elena.messina}@nist.gov 5 (Received: 24 March 2004; in final form: 2 September 2005) 6 Abstract. An iterative temporal registration algorithm is presented in this article for registering 8 3D range images obtained from unmanned ground and aerial vehicles traversing unstructured 9 environments. We are primarily motivated by the development of 3D registration algorithms to 10 overcome both the unavailability and unreliability of Global Positioning System (GPS) within 11 required accuracy bounds for Unmanned Ground Vehicle (UGV) navigation. After suitable 12 modifications to the well-known Iterative Closest Point (ICP) algorithm, the modified algorithm is 13 shown to be robust to outliers and false matches during the registration of successive range images 14 obtained from a scanning LADAR rangefinder on the UGV. Towards registering LADAR images 15 from the UGV with those from an Unmanned Aerial Vehicle (UAV) that flies over the terrain 16 being traversed, we then propose a hybrid registration approach. In this approach to air to ground 17 registration to estimate and update the position of the UGV, we register range data from two 18 LADARs by combining a feature-based method with the aforementioned modified ICP algorithm. 19 Registration of range data guarantees an estimate of the vehicle’s position even when only one of 20 the vehicles has GPS information. -
Concept and Functional Structure of a Service Robot
International Journal of Advanced Robotic Systems ARTICLE Concept and Functional Structure of a Service Robot Regular Paper Luis A. Pineda1*, Arturo Rodríguez1, Gibran Fuentes1, Caleb Rascon1 and Ivan V. Meza1 1 National Autonomous University of Mexico, Mexico * Corresponding author(s) E-mail: [email protected] Received 13 June 2014; Accepted 28 November 2014 DOI: 10.5772/60026 © 2015 The Author(s). Licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract reflection upon the present concept of a service robot and its associated functional specifications, and the potential In this paper, we present a concept of service robot and a impact of such a conceptual model in the study, develop‐ framework for its functional specification and implemen‐ ment and application of service robots in general. tation. The present discussion is grounded in Newell’s system levels hierarchy which suggests organizing robotics Keywords Concept of a service robot, Service robots research in three different layers, corresponding to Marr’s system levels, Conceptual model of service robots, Robot‐ computational, algorithmic and implementation levels, as ics’ task structure, Practical tasks, Structure of a general follows: (1) the service robot proper, which is the subject of purpose service robot, RoboCup@Home competition, The the present paper, (2) perception and action algorithms, Golem-II+ robot and (3) the systems programming level. The concept of a service robot is articulated in practice through the intro‐ duction of a conceptual model for particular service robots; this consists of the specification of a set of basic robotic 1. -
Dynamic Reconfiguration of Mission Parameters in Underwater Human
Dynamic Reconfiguration of Mission Parameters in Underwater Human-Robot Collaboration Md Jahidul Islam1, Marc Ho2, and Junaed Sattar3 Abstract— This paper presents a real-time programming and in the underwater domain, what would otherwise be straight- parameter reconfiguration method for autonomous underwater forward deployments in terrestrial settings often become ex- robots in human-robot collaborative tasks. Using a set of tremely complex undertakings for underwater robots, which intuitive and meaningful hand gestures, we develop a syntacti- cally simple framework that is computationally more efficient require close human supervision. Since Wi-Fi or radio (i.e., than a complex, grammar-based approach. In the proposed electromagnetic) communication is not available or severely framework, a convolutional neural network is trained to provide degraded underwater [7], such methods cannot be used accurate hand gesture recognition; subsequently, a finite-state to instruct an AUV to dynamically reconfigure command machine-based deterministic model performs efficient gesture- parameters. The current task thus needs to be interrupted, to-instruction mapping and further improves robustness of the interaction scheme. The key aspect of this framework is and the robot needs to be brought to the surface in order that it can be easily adopted by divers for communicating to reconfigure its parameters. This is inconvenient and often simple instructions to underwater robots without using artificial expensive in terms of time and physical resources. Therefore, tags such as fiducial markers or requiring memorization of a triggering parameter changes based on human input while the potentially complex set of language rules. Extensive experiments robot is underwater, without requiring a trip to the surface, are performed both on field-trial data and through simulation, which demonstrate the robustness, efficiency, and portability of is a simpler and more efficient alternative approach. -
Robots Are Becoming Autonomous
FORSCHUNGSAUSBLICK 02 RESEARCH OUTLOOK STEFAN SCHAAL MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS, TÜBINGEN Robots are becoming autonomous Towards the end of the 1990s Japan launched a globally or carry out complex manipulations are still in the research unique wave of funding of humanoid robots. The motivation stage. Research into humanoid robots and assistive robots is was clearly formulated: demographic trends with rising life being pursued around the world. Problems such as the com- expectancy and stagnating or declining population sizes in plexity of perception, effective control without endangering highly developed countries will create problems in the fore- the environment and a lack of learning aptitude and adapt- seeable future, in particular with regard to the care of the ability continue to confront researchers with daunting chal- elderly due to a relatively sharp fall in the number of younger lenges for the future. Thus, an understanding of autonomous people able to help the elderly cope with everyday activities. systems remains essentially a topic of basic research. Autonomous robots are a possible solution, and automotive companies like Honda and Toyota have invested billions in a AUTONOMOUS ROBOTICS: PERCEPTION–ACTION– potential new industrial sector. LEARNING Autonomous systems can be generally characterised as Today, some 15 years down the line, the challenge of “age- perception-action-learning systems. Such systems should ing societies” has not changed, and Europe and the US have be able to perform useful tasks for extended periods autono- also identified and singled out this very problem. But new mously, meaning without external assistance. In robotics, challenges have also emerged. Earthquakes and floods cause systems have to perform physical tasks and thus have to unimaginable damage in densely populated areas. -
Service Robots Are Increasingly Broadening Our Horizons Beyond the Factory Floor
Toward a Science of Autonomy for Physical Systems: Service Peter Allen Henrik I. Christensen [email protected] [email protected] Columbia University Georgia Institute of Technology Computing Community Consortium Version 1: June 23, 20151 1 Overview A recent study by the Robotic Industries Association [2] has highlighted how service robots are increasingly broadening our horizons beyond the factory floor. From robotic vacuums, bomb retrievers, exoskeletons and drones, to robots used in surgery, space exploration, agriculture, home assistance and construction, service robots are building a formidable resume. In just the last few years we have seen service robots deliver room service meals, assist shoppers in finding items in a large home improvement store, checking in customers and storing their luggage at hotels, and pour drinks on cruise ships. Personal robots are here to educate, assist and entertain at home. These domestic robots can perform daily chores, assist people with disabilities and serve as companions or pets for entertainment [1]. By all accounts, the growth potential for service robotics is quite large [2, 3]. Due to their multitude of forms and structures as well as application areas, service robots are not easy to define. The International Federation of Robots (IFR) has created some preliminary definitions of service robots [5]. A service robot is a robot that performs useful tasks for humans or equipment excluding industrial automation applications. Some examples are domestic servant robots, automated wheelchairs, and personal mobility assist robots. A service robot for professional use is a service robot used for a commercial task, usually operated by a properly trained operator. -
Service Robots 7 Mouser Staff
1 1 TABLE OF CONTENTS Welcome from the Editor 3 Deborah S. Ray Foreword 6 Grant Imahara Introduction to Service Robots 7 Mouser Staff Sanbot Max: Anatomy of a Service Robot 11 Steven Keeping CIMON Says: Design Lessons from a Robot Assistant in Space 17 Traci Browne 21 Revisiting the Uncanny Valley Jon Gabay Robotic Hands Strive for Human Capabilities 25 Bill Schweber Robotic Gesturing Meets Sign Language 30 Bill Schweber Mouser and Mouser Electronics are registered trademarks of Mouser Electronics, Inc. Other products, logos, and company names mentioned herein may be trademarks of their respective owners. Reference designs, conceptual illustrations, and other graphics included herein are for informational purposes only. Copyright © 2018 Mouser Electronics, Inc. – A TTI and Berkshire Hathaway company. 2 WELCOME FROM THE EDITOR If you’re just now joining us for favorite robots from our favorite This eBook accompanies EIT Video Mouser’s 2018 Empowering shows and movies: Star Wars, Star #3, which features the Henn na Innovation Together™ (EIT) program, Trek, Lost in Space, and Dr. Who. Hotel, the world’s first hotel staffed welcome! This year’s EIT program— by robots. Geared toward efficiency Generation Robot—explores robotics In this EIT segment, we explore and customer comfort, these robots as a technology capable of impacting service robots, which combine not only provide an extraordinary and changing our lives in the 21st principles of automation with that experience of efficiency and comfort, century much like the automobile of robotics to assist humans with but also a fascinating and heart- impacted the 20th century and tasks that are dirty, dangerous, heavy, warming experience for guests.