Language Grounding In Robots
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Language Grounding In Robots
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Author : Luc Steels
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-14
Language Grounding In Robots written by Luc Steels and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-14 with Computers categories.
Written by leading international experts, this volume presents contributions establishing the feasibility of human language-like communication with robots. The book explores the use of language games for structuring situated dialogues in which contextualized language communication and language acquisition can take place. Within the text are integrated experiments demonstrating the extensive research which targets artificial language evolution. Language Grounding in Robots uses the design layers necessary to create a fully operational communicating robot as a framework for the text, focusing on the following areas: Embodiment; Behavior; Perception and Action; Conceptualization; Language Processing; Whole Systems Experiments. This book serves as an excellent reference for researchers interested in further study of artificial language evolution.
Language Grounding In Robots
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Author : Luc Steels
language : en
Publisher: Springer
Release Date : 2014-04-16
Language Grounding In Robots written by Luc Steels and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-16 with Computers categories.
Written by leading international experts, this volume presents contributions establishing the feasibility of human language-like communication with robots. The book explores the use of language games for structuring situated dialogues in which contextualized language communication and language acquisition can take place. Within the text are integrated experiments demonstrating the extensive research which targets artificial language evolution. Language Grounding in Robots uses the design layers necessary to create a fully operational communicating robot as a framework for the text, focusing on the following areas: Embodiment; Behavior; Perception and Action; Conceptualization; Language Processing; Whole Systems Experiments. This book serves as an excellent reference for researchers interested in further study of artificial language evolution.
Adaptive Perception For Efficient Spatio Temporal Language Grounding In Dynamic Environments
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Author : Siddharth Patki
language : en
Publisher:
Release Date : 2023
Adaptive Perception For Efficient Spatio Temporal Language Grounding In Dynamic Environments written by Siddharth Patki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
"As robots are becoming increasingly prevalent in shared spaces such as homes and offices, the need for efficient and effective human-robot collaboration has become imperative. One of the key aspects of human-robot collaboration is the ability of robots to understand and interpret human instructions. However, the challenges associated with understanding natural language instructions in cluttered and dynamic environments remain significant. Recent approaches to grounded language understanding reason only in the context of an instantaneous state of the world. Though this allows for interpreting a variety of utterances in the current context of the world, these models fail to interpret utterances which require the knowledge of past dynamics of the world, thereby hindering effective human-robot collaboration in dynamic environments. Extending the contemporary models to reason about utterances which require knowledge of the past dynamics of the world introduces non-trivial challenges related to to both world state estimation and symbol grounding. Specifically in relation to world modeling, constructing a comprehensive model of the dynamic world that tracks the states of all objects in the robot's workspace is computationally intractable and difficult to scale with increasing clutter in the environments. On the other hand, a poorly detailed model of the environment limits the diversity of the utterances that can be interpreted and executed. A fundamental research question then is, how to efficiently reason over this rich information in a manner that enables robots to efficiently execute a variety of instructions in highly cluttered and dynamic worlds. In this thesis I present an arc of research which investigates how the information in language can be utilized to construct task-specific representations of the world, enabling faster and more accurate symbol grounding in cluttered and dynamic environments. Specifically, first this thesis presents a learned model of language and perception called Language Guided Adaptive Perception (LG-AP) that allows language to steer the interpretation of raw observations to create world models that are minimal but sufficient for the grounding robot instructions in static environments. Second, this thesis presents a novel approach called Language Guided Temporally Adaptive Perception (LG-TAP), that facilitates the construction of temporally compact models of dynamic worlds through closed-loop grounding and perception. This document includes is a discussion of the synergies that exist among these contributions and how adapting perception by exploiting the information in language can improve runtime efficiency and accuracy of robot instruction following in static and dynamic environments with high degree of clutter."--Pages xii-xiii.
Spatial Language For Mobile Robots
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Author :
language : en
Publisher:
Release Date : 2008
Spatial Language For Mobile Robots written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Language acquisition categories.
Experimental Robotics
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Author : Oussama Khatib
language : en
Publisher: Springer
Release Date : 2013-08-20
Experimental Robotics written by Oussama Khatib and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-20 with Technology & Engineering categories.
Incorporating papers from the 12th International Symposium on Experimental Robotics (ISER), December 2010, this book examines the latest advances across the various fields of robotics. Offers insights on both theoretical concepts and experimental results.
Continually Improving Grounded Natural Language Understanding Through Human Robot Dialog
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Author : Jesse David Thomason
language : en
Publisher:
Release Date : 2018
Continually Improving Grounded Natural Language Understanding Through Human Robot Dialog written by Jesse David Thomason and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
As robots become ubiquitous in homes and workplaces such as hospitals and factories, they must be able to communicate with humans. Several kinds of knowledge are required to understand and respond to a human's natural language commands and questions. If a person requests an assistant robot to take me to Alice's office, the robot must know that Alice is a person who owns some unique office, and that take me means it should navigate there. Similarly, if a person requests bring me the heavy, green mug, the robot must have accurate mental models of the physical concepts heavy, green, and mug. To avoid forcing humans to use key phrases or words robots already know, this thesis focuses on helping robots understanding new language constructs through interactions with humans and with the world around them. To understand a command in natural language, a robot must first convert that command to an internal representation that it can reason with. Semantic parsing is a method for performing this conversion, and the target representation is often semantic forms represented as predicate logic with lambda calculus. Traditional semantic parsing relies on hand-crafted resources from a human expert: an ontology of concepts, a lexicon connecting language to those concepts, and training examples of language with abstract meanings. One thrust of this thesis is to perform semantic parsing with sparse initial data. We use the conversations between a robot and human users to induce pairs of natural language utterances with the target semantic forms a robot discovers through its questions, reducing the annotation effort of creating training examples for parsing. We use this data to build more dialog-capable robots in new domains with much less expert human effort (Thomason et al., 2015; Padmakumar et al., 2017). Meanings of many language concepts are bound to the physical world. Understanding object properties and categories, such as heavy, green, and mug requires interacting with and perceiving the physical world. Embodied robots can use manipulation capabilities, such as pushing, picking up, and dropping objects to gather sensory data about them. This data can be used to understand non-visual concepts like heavy and empty (e.g. get the empty carton of milk from the fridge), and assist with concepts that have both visual and non-visual expression (e.g. tall things look big and also exert force sooner than short things when pressed down on). A second thrust of this thesis focuses on strategies for learning these concepts using multi-modal sensory information. We use human-in-the-loop learning to get labels between concept words and actual objects in the environment (Thomason et al., 2016, 2017). We also explore ways to tease out polysemy and synonymy in concept words (Thomason and Mooney, 2017) such as light, which can refer to a weight or a color, the latter sense being synonymous with pale. Additionally, pushing, picking up, and dropping objects to gather sensory information is prohibitively time-consuming, so we investigate strategies for using linguistic information and human input to expedite exploration when learning a new concept (Thomason et al., 2018). Finally, we build an integrated agent with both parsing and perception capabilities that learns from conversations with users to improve both components over time. We demonstrate that parser learning from conversations (Thomason et al., 2015) can be combined with multi-modal perception (Thomason et al., 2016) using predicate-object labels gathered through opportunistic active learning (Thomason et al., 2017) during those conversations to improve performance for understanding natural language commands from humans. Human users also qualitatively rate this integrated learning agent as more usable after it has improved from conversation-based learning.
How Mobile Robots Can Self Organise A Vocabulary
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Author : Paul Vogt
language : en
Publisher:
Release Date : 2017-05-05
How Mobile Robots Can Self Organise A Vocabulary written by Paul Vogt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-05 with Mobile robots categories.
One of the hardest problems in science is the symbol grounding problem, a question that has intrigued philosophers and linguists for more than a century. With the rise of artificial intelligence, the question has become very actual, especially within the field of robotics. The problem is that an agent, be it a robot or a human, perceives the world in analogue signals. Yet humans have the ability to categorise the world in symbols that they, for instance, may use for language. This book presents a series of experiments in which two robots try to solve the symbol grounding problem. The experiments are based on the language game paradigm, and involve real mobile robots that are able to develop a grounded lexicon about the objects that they can detect in their world. Crucially, neither the lexicon nor the ontology of the robots has been preprogrammed, so the experiments demonstrate how a population of embodied language users can develop their own vocabularies from scratch.
Dcg Upup Away
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Author : Mycal D. Tucker
language : en
Publisher:
Release Date : 2016
Dcg Upup Away written by Mycal D. Tucker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Research in automatic natural language grounding, in which robots understand how phrases relate to real-world objects or actions, offers a compelling reality in which untrained humans can operate highly sophisticated robots. Current techniques for training robots to understand natural language, however, assume that there is a fixed set of phrases or objects that the robot will encounter during deployment. Instead, the real world is full of confusing jargon and unique objects that are nearly impossible to anticipate and therefore train for. This thesis presents a model called the Distributed Correspondence Graph - Unknown Phrase, Unknown Percept - Away (DCG-UPUP-Away) that augments the state of the art Distributed Correspondence Graph by recognizing unknown phrases and objects as unknown, as well as reasoning about objects that are not currently perceived. Furthermore, experimental results in simulation, as well as a trial run on a turtlebot platform, validate the effectiveness of DCG-UPUP-Away in grounding phrases and learning new phrases.
Natural Language Understanding And Cognitive Robotics
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Author : Masao Yokota
language : en
Publisher: CRC Press
Release Date : 2019-12-06
Natural Language Understanding And Cognitive Robotics written by Masao Yokota and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-06 with Technology & Engineering categories.
In the not so distant future, we can expect a world where humans and robots coexist and interact with each other. For this to occur, we need to understand human traits, such as seeing, hearing, thinking, speaking, etc., and institute these traits in robots. The most essential feature necessary for robots to achieve is that of integrative multimedia understanding (IMU) which occurs naturally in humans. It allows us to assimilate pieces of information expressed through different modes such as speech, pictures, gestures, etc. The book describes how robots acquire traits like natural language understanding (NLU) as the central part of IMU. Mental image directed semantic theory (MIDST) is its core, and is based on the hypothesis that NLU is essentially the processing of mental image associated with natural language expressions, namely, mental-image based understanding (MBU). MIDST is intended to model omnisensory mental image in human and to afford a knowledge representation system in order for integrative management of knowledge subjective to cognitive mechanisms of intelligent entities such as humans and robots based on a mental image model visualized as ‘Loci in Attribute Spaces’ and its description language Lmd (mental image description language) to be employed for predicate logic with a systematic scheme for symbol-grounding. This language works as an interlingua among various kinds of information media, and has been applied to several versions of the intelligent system interlingual understanding model aiming at general system (IMAGES). Its latest version, i.e. conversation management system (CMS) simulates MBU and comprehends the user’s intention through dialogue to find and solve problems, and finally, provides a response in text or animation. The book is aimed at researchers and students interested in artificial intelligence, robotics, and cognitive science. Based on philosophical considerations, the methodology will also have an appeal in linguistics, psychology, ontology, geography, and cartography. Key Features: Describes the methodology to provide robots with human-like capability of natural language understanding (NLU) as the central part of IMU Uses methodology that also relates to linguistics, psychology, ontology, geography, and cartography Examines current trends in machine translation
Talking To Robots
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Author : Cynthia Matuszek
language : en
Publisher:
Release Date : 2014
Talking To Robots written by Cynthia Matuszek and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Advances in computation, sensing, and hardware are enabling robots to perform an increasing variety of tasks in progressively fewer constraints. It is now possible to imagine robots that can operate in traditionally human-centric environments. However, such robots need the flexibility to take instructions and learn about tasks from nonspecialists using language and other natural modalities. At the same time, physically grounded settings provide exciting opportunities for language learning. This thesis describes work on learning to acquire language for human-robot interaction in a physically grounded space. Two use cases are considered: learning to follow route directions through an indoor map, and learning about object attributes from people using unconstrained language and gesture. These problems are challenging because both language and real-world sensing tend to be noisy and ambiguous. This is addressed by reasoning and learning jointly about language and its physical context, parsing into intermediate formal representations that can be interpreted meaningfully by robotic systems. These systems can learn how to follow natural language directions through a map and how to identify objects from human descriptions, even when the underlying concepts are novel to the system, with success rates comparable to or defining the state of the art. Evaluations show that this work takes important steps towards building a robust, flexible, and effective mechanism for bringing together language acquisition and sensing to learn about the world.