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Book Reasoning with Uncertainty in Robotics

Download or read book Reasoning with Uncertainty in Robotics written by Leo Dorst and published by Lecture Notes in Artificial Intelligence. This book was released on 1996-06-12 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the International Workshop on Reasoning with Uncertainty in Robotics, RUR'95, held in Amsterdam, The Netherlands, in December 1995. The book contains 13 revised full papers carefully selected for presentation during the workshop together with six invited papers. Also included are two comprehensive tutorial texts and an introduction by the volume editors. Thus the book is both a competent state-of-the-art report on current research and development and a valuable survey and introduction for researchers entering the area or professionals interested in the application of up-to-date techniques.

Book Reasoning about Uncertainty in Robot Motion Planning

Download or read book Reasoning about Uncertainty in Robot Motion Planning written by Anthony Lazanas and published by . This book was released on 1994 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experimentation with the algorithm using a real mobile robot has been successful. By engineering the workspace, we have been able to satisfy all the assumptions of our planning model. As a result, the robot has been able to operate for long periods of time with no failures.

Book Reasoning with Uncertainty in Robotics

Download or read book Reasoning with Uncertainty in Robotics written by Leo Dorst and published by Springer. This book was released on 2014-03-12 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the International Workshop on Reasoning with Uncertainty in Robotics, RUR'95, held in Amsterdam, The Netherlands, in December 1995. The book contains 13 revised full papers carefully selected for presentation during the workshop together with six invited papers. Also included are two comprehensive tutorial texts and an introduction by the volume editors. Thus the book is both a competent state-of-the-art report on current research and development and a valuable survey and introduction for researchers entering the area or professionals interested in the application of up-to-date techniques.

Book Reasoning Robots

    Book Details:
  • Author : Michael Thielscher
  • Publisher : Springer Science & Business Media
  • Release : 2005-12-15
  • ISBN : 140203069X
  • Pages : 334 pages

Download or read book Reasoning Robots written by Michael Thielscher and published by Springer Science & Business Media. This book was released on 2005-12-15 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The creation of intelligent robots is surely one of the most exciting and ch- lenginggoals of Arti?cial Intelligence. A robot is, ?rst of all, nothing but an inanimate machine with motors and sensors. In order to bring life to it, the machine needs to be programmed so as to make active use of its hardware c- ponents. This turns a machine into an autonomous robot. Since about the mid nineties of the past century, robot programming has made impressive progress. State-of-the-art robots are able to orient themselves and move around freely in indoor environments or negotiate di?cult outdoor terrains, they can use stereo vision to recognize objects, and they are capable of simple object manipulation with the help of arti?cial extremities. At a time where robots perform these tasks more and more reliably,weare ready to pursue the next big step, which is to turn autonomous machines into reasoning robots.Areasoning robot exhibits higher cognitive capabilities like following complex and long-term strategies, making rational decisions on a high level, drawing logical conclusions from sensor information acquired over time, devising suitable plans, and reacting sensibly in unexpected situations. All of these capabilities are characteristics of human-like intelligence and ultimately distinguish truly intelligent robots from mere autonomous machines.

Book Robust Stream Reasoning Under Uncertainty

Download or read book Robust Stream Reasoning Under Uncertainty written by Daniel de Leng and published by Linköping University Electronic Press. This book was released on 2019-11-08 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vast amounts of data are continually being generated by a wide variety of data producers. This data ranges from quantitative sensor observations produced by robot systems to complex unstructured human-generated texts on social media. With data being so abundant, the ability to make sense of these streams of data through reasoning is of great importance. Reasoning over streams is particularly relevant for autonomous robotic systems that operate in physical environments. They commonly observe this environment through incremental observations, gradually refining information about their surroundings. This makes robust management of streaming data and their refinement an important problem. Many contemporary approaches to stream reasoning focus on the issue of querying data streams in order to generate higher-level information by relying on well-known database approaches. Other approaches apply logic-based reasoning techniques, which rarely consider the provenance of their symbolic interpretations. In this work, we integrate techniques for logic-based stream reasoning with the adaptive generation of the state streams needed to do the reasoning over. This combination deals with both the challenge of reasoning over uncertain streaming data and the problem of robustly managing streaming data and their refinement. The main contributions of this work are (1) a logic-based temporal reasoning technique based on path checking under uncertainty that combines temporal reasoning with qualitative spatial reasoning; (2) an adaptive reconfiguration procedure for generating and maintaining a data stream required to perform spatio-temporal stream reasoning over; and (3) integration of these two techniques into a stream reasoning framework. The proposed spatio-temporal stream reasoning technique is able to reason with intertemporal spatial relations by leveraging landmarks. Adaptive state stream generation allows the framework to adapt to situations in which the set of available streaming resources changes. Management of streaming resources is formalised in the DyKnow model, which introduces a configuration life-cycle to adaptively generate state streams. The DyKnow-ROS stream reasoning framework is a concrete realisation of this model that extends the Robot Operating System (ROS). DyKnow-ROS has been deployed on the SoftBank Robotics NAO platform to demonstrate the system's capabilities in a case study on run-time adaptive reconfiguration. The results show that the proposed system - by combining reasoning over and reasoning about streams - can robustly perform stream reasoning, even when the availability of streaming resources changes.

Book Uncertainty in Artificial Intelligence 5

Download or read book Uncertainty in Artificial Intelligence 5 written by Max Henrion and published by North Holland. This book was released on 1990-01 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty. A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language understanding.

Book Probabilistic Robotics

Download or read book Probabilistic Robotics written by Sebastian Thrun and published by MIT Press. This book was released on 2005-08-19 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

Book Reasoning about Uncertainty  second edition

Download or read book Reasoning about Uncertainty second edition written by Joseph Y. Halpern and published by MIT Press. This book was released on 2017-04-07 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Formal ways of representing uncertainty and various logics for reasoning about it; updated with new material on weighted probability measures, complexity-theoretic considerations, and other topics. In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty. Halpern surveys possible formal systems for representing uncertainty, including probability measures, possibility measures, and plausibility measures; considers the updating of beliefs based on changing information and the relation to Bayes' theorem; and discusses qualitative, quantitative, and plausibilistic Bayesian networks. This second edition has been updated to reflect Halpern's recent research. New material includes a consideration of weighted probability measures and how they can be used in decision making; analyses of the Doomsday argument and the Sleeping Beauty problem; modeling games with imperfect recall using the runs-and-systems approach; a discussion of complexity-theoretic considerations; the application of first-order conditional logic to security. Reasoning about Uncertainty is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics.

Book Probabilistic Approaches to Robotic Perception

Download or read book Probabilistic Approaches to Robotic Perception written by João Filipe Ferreira and published by Springer. This book was released on 2013-08-30 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book tries to address the following questions: How should the uncertainty and incompleteness inherent to sensing the environment be represented and modelled in a way that will increase the autonomy of a robot? How should a robotic system perceive, infer, decide and act efficiently? These are two of the challenging questions robotics community and robotic researchers have been facing. The development of robotic domain by the 1980s spurred the convergence of automation to autonomy, and the field of robotics has consequently converged towards the field of artificial intelligence (AI). Since the end of that decade, the general public’s imagination has been stimulated by high expectations on autonomy, where AI and robotics try to solve difficult cognitive problems through algorithms developed from either philosophical and anthropological conjectures or incomplete notions of cognitive reasoning. Many of these developments do not unveil even a few of the processes through which biological organisms solve these same problems with little energy and computing resources. The tangible results of this research tendency were many robotic devices demonstrating good performance, but only under well-defined and constrained environments. The adaptability to different and more complex scenarios was very limited. In this book, the application of Bayesian models and approaches are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems, inherently dealing with uncertainty and the “irreducible incompleteness of models”.

Book Incrementally Increasing the Uncertainty tolerance of Robotic Manipulation Plans

Download or read book Incrementally Increasing the Uncertainty tolerance of Robotic Manipulation Plans written by Scott Bennett and published by . This book was released on 1991 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Last, unguaranteed but practical plans can be generated by the incremental approach when they lie outside the scope of the guaranteed planner. To demonstrate our approach we describe an implemented system called GRASPER which learns to grasp novel objects given only imprecise television camera input. No prior model of the objects is assumed, nor are the objects required to satisfy a priori constraints on their shapes. Robustness of the system's grasping improves with experience."

Book Algorithmic Foundations of Robotics X

Download or read book Algorithmic Foundations of Robotics X written by Emilio Frazzoli and published by Springer. This book was released on 2013-02-14 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are a fundamental component of robotic systems. Robot algorithms process inputs from sensors that provide noisy and partial data, build geometric and physical models of the world, plan high-and low-level actions at different time horizons, and execute these actions on actuators with limited precision. The design and analysis of robot algorithms raise a unique combination of questions from many elds, including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track meeting of leading researchers in the eld of robot algorithms. Since its inception in 1994, WAFR has been held every other year, and has provided one of the premiere venues for the publication of some of the eld's most important and lasting contributions. This books contains the proceedings of the tenth WAFR, held on June 13{15 2012 at the Massachusetts Institute of Technology. The 37 papers included in this book cover a broad range of topics, from fundamental theoretical issues in robot motion planning, control, and perception, to novel applications.

Book Algorithmic Foundations of Robotics XIV

Download or read book Algorithmic Foundations of Robotics XIV written by Steven M. LaValle and published by Springer Nature. This book was released on 2021-02-08 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book helps bring insights from this array of technical sub-topics together, as advanced robot algorithms draw on the combined expertise of many fields—including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. Intelligent robots and autonomous systems depend on algorithms that efficiently realize functionalities ranging from perception to decision making, from motion planning to control. The works collected in this SPAR book represent the state of the art in algorithmic robotics. They originate from papers accepted to the 14th International Workshop on the Algorithmic Foundations of Robotics (WAFR), traditionally a biannual, single-track meeting of leading researchers in the field of robotics. WAFR has always served as a premiere venue for the publication of some of robotics’ most important, fundamental, and lasting algorithmic contributions, ensuring the rapid circulation of new ideas. Though an in-person meeting was planned for June 15–17, 2020, in Oulu, Finland, the event ended up being canceled owing to the infeasibility of international travel during the global COVID-19 crisis.

Book Planning and Decision Making for Aerial Robots

Download or read book Planning and Decision Making for Aerial Robots written by Yasmina Bestaoui Sebbane and published by Springer Science & Business Media. This book was released on 2014-01-10 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the emerging field of planning and decision making for aerial robots. An aerial robot is the ultimate form of Unmanned Aerial Vehicle, an aircraft endowed with built-in intelligence, requiring no direct human control and able to perform a specific task. It must be able to fly within a partially structured environment, to react and adapt to changing environmental conditions and to accommodate for the uncertainty that exists in the physical world. An aerial robot can be termed as a physical agent that exists and flies in the real 3D world, can sense its environment and act on it to achieve specific goals. So throughout this book, an aerial robot will also be termed as an agent. Fundamental problems in aerial robotics include the tasks of spatial motion, spatial sensing and spatial reasoning. Reasoning in complex environments represents a difficult problem. The issues specific to spatial reasoning are planning and decision making. Planning deals with the trajectory algorithmic development based on the available information, while decision making determines priorities and evaluates potential environmental uncertainties. The issues specific to planning and decision making for aerial robots in their environment are examined in this book and categorized as follows: motion planning, deterministic decision making, decision making under uncertainty and finally multi-robot planning. A variety of techniques are presented in this book, and a number of relevant case studies are examined. The topics considered in this book are multidisciplinary in nature and lie at the intersection of Robotics, Control Theory, Operational Research and Artificial Intelligence.

Book Uncertainty Treatment Using Paraconsistent Logic

Download or read book Uncertainty Treatment Using Paraconsistent Logic written by João Inácio da Silva Filho and published by IOS Press. This book was released on 2010 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aggregates much of this research, from 1999 up to the present. Organized to facilitate an understanding of the theory and the development of the applied methods, Uncertainty Treatment Using Praconsistent Logic presents the material in a sequential fashion and is divided into three parts.

Book Qualitative and Quantitative Practical Reasoning

Download or read book Qualitative and Quantitative Practical Reasoning written by Dov Gabbay and published by Springer Science & Business Media. This book was released on 1997-05-28 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Joint Conference on Qualitative and Quantitative Practical Reasoning, ECSQARU-FAPR'97, held in Bad Honnef, Germany, in June 1997. The volume presents 33 revised full papers carefully selected for inclusion in the book by the program committee as well as 12 invited contributions. Among the various aspects of human practical reasoning addressed in the papers are nonmonotonic logics, default reasoning, modal logics, belief function theory, Bayesian networks, fuzzy logic, possibility theory, inference algorithms, dynamic reasoning with partial models, and user modeling approaches.

Book Cognitive Reasoning for Compliant Robot Manipulation

Download or read book Cognitive Reasoning for Compliant Robot Manipulation written by Daniel Sebastian Leidner and published by Springer. This book was released on 2018-12-08 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to achieve human-like performance, this book covers the four steps of reasoning a robot must provide in the concept of intelligent physical compliance: to represent, plan, execute, and interpret compliant manipulation tasks. A classification of manipulation tasks is conducted to identify the central research questions of the addressed topic. It is investigated how symbolic task descriptions can be translated into meaningful robot commands.Among others, the developed concept is applied in an actual space robotics mission, in which an astronaut aboard the International Space Station (ISS) commands the humanoid robot Rollin' Justin to maintain a Martian solar panel farm in a mock-up environment

Book Algorithmic Foundations of Robotics XV

Download or read book Algorithmic Foundations of Robotics XV written by Steven M. LaValle and published by Springer Nature. This book was released on 2022-12-14 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes significant recent research on robotic algorithms. It has been written by leading experts in the field. The 15th Workshop on the Algorithmic Foundations of Robotics (WAFR) was held on June 22–24, 2022, at the University of Maryland, College Park, Maryland. Each chapter represents an exciting state-of-the-art development in robotic algorithms that was presented at this 15th incarnation of WAFR. Different chapters combine ideas from a wide variety of fields, spanning and combining planning (for tasks, paths, motion, navigation, coverage, and patrol), computational geometry and topology, control theory, machine learning, formal methods, game theory, information theory, and theoretical computer science. Many of these papers explore new and interesting problems and problem variants that include human–robot interaction, planning and reasoning under uncertainty, dynamic environments, distributed decision making, multi-agent coordination, and heterogeneity.