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Author: Alberto Maria Segre
Publisher: Springer Science & Business Media
ISBN: 146131691X
Category : Computers
Languages : en
Pages : 244
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Book Description
The study of artificial intelligence (AI) is indeed a strange pursuit. Unlike most other disciplines, few AI researchers even agree on a mutually acceptable definition of their chosen field of study. Some see AI as a sub field of computer science, others see AI as a computationally oriented branch of psychology or linguistics, while still others see it as a bag of tricks to be applied to an entire spectrum of diverse domains. This lack of unified purpose among the AI community makes this a very exciting time for AI research: new and diverse projects are springing up literally every day. As one might imagine, however, this diversity also leads to genuine difficulties in assessing the significance and validity of AI research. These difficulties are an indication that AI has not yet matured as a science: it is still at the point where people are attempting to lay down (hopefully sound) foundations. Ritchie and Hanna [1] posit the following categorization as an aid in assessing the validity of an AI research endeavor: (1) The project could introduce, in outline, a novel (or partly novel) idea or set of ideas. (2) The project could elaborate the details of some approach. Starting with the kind of idea in (1), the research could criticize it or fill in further details (3) The project could be an AI experiment, where a theory as in (1) and (2) is applied to some domain. Such experiments are usually computer programs that implement a particular theory.
Author: Alberto Maria Segre
Publisher: Springer Science & Business Media
ISBN: 146131691X
Category : Computers
Languages : en
Pages : 244
Get Book Here
Book Description
The study of artificial intelligence (AI) is indeed a strange pursuit. Unlike most other disciplines, few AI researchers even agree on a mutually acceptable definition of their chosen field of study. Some see AI as a sub field of computer science, others see AI as a computationally oriented branch of psychology or linguistics, while still others see it as a bag of tricks to be applied to an entire spectrum of diverse domains. This lack of unified purpose among the AI community makes this a very exciting time for AI research: new and diverse projects are springing up literally every day. As one might imagine, however, this diversity also leads to genuine difficulties in assessing the significance and validity of AI research. These difficulties are an indication that AI has not yet matured as a science: it is still at the point where people are attempting to lay down (hopefully sound) foundations. Ritchie and Hanna [1] posit the following categorization as an aid in assessing the validity of an AI research endeavor: (1) The project could introduce, in outline, a novel (or partly novel) idea or set of ideas. (2) The project could elaborate the details of some approach. Starting with the kind of idea in (1), the research could criticize it or fill in further details (3) The project could be an AI experiment, where a theory as in (1) and (2) is applied to some domain. Such experiments are usually computer programs that implement a particular theory.
Author: Alberto Maria Segre
Publisher:
ISBN:
Category :
Languages : en
Pages : 470
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Book Description
This report describes an experiment involving the application of a recently developed machine learning technique, explanation-based learning, to the robot retraining problem. Explanation-based learning permits a system to acquire generalized problem-solving knowledge on the basis of a single observed problem-solving example. The resulting computer program, called ARMS for Acquiring Robotic Manufacturing Schemata, serves as a medium for discussing issues related to this particular type of learning. This work clarifies and extends the corpus of knowledge so that explanation-based learning can be successfully applied to real world problems. From a machine learning perspective, ARMS is one of the more ambitious working explanation-based learning implementations to date. Unlike many other vehicles for machine learning research, the ARMS system operates in a nontrivial domain conveying the flavor of a real robot assembly application. (Keywords: Artificial intelligence; Scenarios).
Author: B. O. Nnaji
Publisher: Springer Science & Business Media
ISBN: 9780412393105
Category : Computers
Languages : en
Pages : 344
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Book Description
Machines will gradually become programmed using computers which have the knowledge of how the objects in the world relate to one another. This book capitalizes on the fact that products which are manufactured can be designed on the computer and that information about the product such as its physical shape provide powerful information to reason about how to develop the process plan for their manufacture. This book explores the whole aspect of using the principles of how parts behave naturally to automatically generate programs that govern how to produce them. The last decade saw tremendous work on how machines can be programmed to perform a variety of tasks automatically. Robotics has witnessed the most work on programming techniques. But it was not until the emergence of the advanced CAD system as a proper source of information representation about objects which are to be manipulated by the robot that it became viable for automated processors to generate robot programs without human interface. It became possible for objects to be described and for principles about how they interact in the world to be developed. The functions which the features designed into the objects serve for the objects can be adequately represented and used in reasoning about the manufacturing of the parts using the robot. This book describes the necessary principles which must be developed for a robot to generate its own programs with the knowledge of the world in the CAD system.
Author: Bhaskaran Gopalakrishnan
Publisher:
ISBN:
Category : Machine learning
Languages : en
Pages : 11
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Book Description
Author: Tony. Owen
Publisher: Springer Science & Business Media
ISBN: 146841500X
Category : Science
Languages : en
Pages : 208
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Book Description
In the western world, economic logic (and need) has replaced the indentured craftsman by computer controlled machining centres within manufacturing industries. The same rationale is the incentive behind the development of robots that are technically capable of performing assembly tasks, and the inevitable, albeit slow, adoption of these robots by the manufacturing industries. This book is based upon the author's knowledge and first hand experience of the manufacturing industries of North America and the UK in general, and the UK's robotics industry in particular. The general and specific implications of per forming an assembly task robotically are discussed, the majority of which are not specific to anyone sector of the manufactur ing industry, nor to any particular size of product being manu factured. This book should be of interest to those who are interested in or involved with the use of robots for assembly. The 'veils of mystic' and misinformation on robots and the assembly process are subsequently removed.
Author: Robin Tommy
Publisher: BPB Publications
ISBN: 939139227X
Category : Computers
Languages : en
Pages : 238
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Book Description
A beginner’s guide to learn ROS, robotics platform, and practice building robotics system KEY FEATURES ● A step-by-step guide covering the robot's design, assembly, navigation and control. ● Numerous techniques, ROS packages, object detection and image processing concepts included. ● Practical exercises and sample codes to robotics design, simulation, and visualization tools. DESCRIPTION This book is a practical introduction to the Robotics operating system (ROS). It will expose you to the essential principles, tools, and packages in ROS and assist you in configuring and recombining components for additional tasks. If you are new to the world of robotics, you will enjoy the companionship of this book as it guides you through the process of building your first robot. The book introduces robotics and advances through numerous concepts such as sensors and actuators, SLAM, Aruco markers, CAD (computer-aided design), React native application development, image processing in ROS, machine learning and object detection. Every point raised above is illustrated in a live robotics environment. Along the way, other packages required for developing ROS apps will be presented, including serial, OpenCV, and cv bridge. You'll learn about tools like SolidWorks, Moveit, Rviz, as well as simulation platforms like gazebo and turtlesim, which will give you a complete picture of what it takes to build a robot. This book presents an in-depth examination of Robot Operating Systems (ROS), the sole foundation for developing robotics applications. The book guides the readers through investigating and embedding machine learning code to introduce intelligence into the robot. WHAT YOU WILL LEARN ● Develop a stronghold on basics of robotics with code samples and illustrations. ● Familiarity with ROS, the configuration of nodes, and 3D robot simulations. ● Learn how to publish data to the ROS network for web integration. ● Learn about SLAM, CAD, React Native, and ROS image processing. ● Learn about Artificial Intelligence principles and object detection with ROS. ● Complete design, simulation, and assembly of a robot. WHO THIS BOOK IS FOR The book is aimed at robotics developers, hardware product designers, full-stack application developers, machine learning enthusiasts, and students who want to obtain real-world experience in robotics development from start to finish. Having some experience with Ubuntu and the python programming language would be helpful. TABLE OF CONTENTS 1. ROS 2. Writing Nodes 3. Sensors and Actuators 4. ROS SERIAL 5. Web interface 6. Turtle Sim Simulation 7. Designing a robot 8. Gazebo 9. Moveit 10. Rviz 11. Vision 12. Aruco Markers 13. SLAM 14. React Native App 15. Artificial Intelligence
Author: Kyle Jordan Brown
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This thesis presents algorithms for multi-agent robotic assembly planning in automated manufacturing contexts. Our work touches on many pieces of the "factory autonomy stack." The first contribution of the thesis is the introduction of a discrete factory problem formulation that includes time-extended multi robot task allocation, inter-task precedence constraints, and collision-avoidance constraints. We propose an efficient method to solve such problems. The two keys to our algorithm's efficiency are its decoupling of task assignment and route planning, and its ability to take advantage of situations where some robots can be delayed in their own schedule without causing any negative impact on the factory's overall performance. The next major contribution of the thesis is a family of replanning algorithms geared toward an online version of our discrete factory problem. In the online setting, the factory command center periodically receives new manufacturing workloads that must be quickly incorporated into the overall schedule. We show through an extensive set of experiments that our replanning methods are applicable across a wide range of problems. Moreover, our proposed methods can be applied in such a way that the factory will never have to freeze while waiting to receive an updated plan. Our final contribution is a proof-of-concept system for large scale multi-robot assembly planning with assemblies and raw materials of arbitrary shapes and sizes. Our system starts with raw materials and a bare-bones set of instructions about how those materials fit together. The planner then synthesizes a construction plan, which defines how each payload will be carried (by one or more robots), where each assembly and subassembly will be built, and which specific robots will be assigned to each solo and collaborative transport task. Finally, a reactive collision-avoidance control policy enables the robots to execute the construction plan in a distributed manner. We demonstrate in simulation that our system can synthesize--in minutes--construction plans for assemblies with hundred of components. Though we do not address all of the relevant ``real-world'' considerations that surround multi robot manufacturing, our work is a small step toward large scale automated construction with mobile robots.
Author: M H Lee
Publisher: World Scientific
ISBN: 9814499579
Category : Computers
Languages : en
Pages : 272
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Book Description
This book deals with a key area of industrial robotics — the automation of small batch assembly. Assembly imparts enormous added value but turns out to be extraordinarily difficult to automate. The work presented here, all from the Centre for Intelligent Systems at the University of Wales, Aberystwyth, addresses this issue and shows ways in which the difficulties may be reduced through systematic architectural designs and specific structures for interfacing and controlling sensory-actuation systems. The book develops three main themes: a task-centred approach to robotic assembly, explicit reasoning techniques for fault diagnosis and error handling; and sensor-actuator integration methods. These are vital topics for those concerned with flexible automation and robotics.
Author: Kathleen Sofia Hajash
Publisher:
ISBN:
Category :
Languages : en
Pages : 76
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Book Description
Since robots were first invented, robotic assembly has been an important area of research in both academic institutions and industry settings. The standard industry approach to robotic assembly lines utilizes fixed robotic arms and prioritizes speed and precision over customization. With a recent shift towards mobile multi-robot teams, researchers have developed a variety of approaches ranging from planning with uncertainty to swarm robotics. However, existing approaches to robotic assembly are either too rigid, with a deterministic planning approach, or do not take advantage of the opportunities available with multiple robots. If we are to push the boundaries of robotic assembly, then we need to make collaborative robots that can work together, without human intervention, to plan and build large structures that they could not complete alone. By developing teams of robots that can collaboratively work together to plan and build large structures, we could aid in disaster relief, enable construction in remote locations, and support the health of construction workers in hazardous environments. In this thesis, I take a first step towards this vision by developing a simple collaborative task wherein agents learn to work together to move rectilinear blocks. I define robotic collaboration as an emergent process that evolves as multiple agents, simulated or physical, learn to work together to achieve a common goal that they could not achieve in isolation. Rather than taking an explicit planning approach, I employ an area of research in artificial intelligence called reinforcement learning, where agents learn an optimal behavior to achieve a specific goal by receiving rewards or penalties for good and bad behavior, respectively. In this thesis, I defined a framework for training the agents and a goal for them to accomplish. I designed, programmed and built two iterations of physical robots. I developed numerous variations of simulation environments for both single and multiple agents, evaluated reinforcement learning algorithms and selected an approach, and established a method for transferring a trained policy to physical robots.
Author: Keith Rathmill
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 392
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Book Description
Setting out relevant examples of state-of-the-art developments and products, this book examines manipulator design, case studies, the importance of product design, programming systems, sensors, and financial issues.
