A kinematically redundant manipulator is a serial robotic arm that has more independently driven joints than are necessary to define the desired pose (position and orientation) of its end-effector. With this definition, any planar manipulator (a manipulator whose end-effector motion is restrained in a plane) with more than three joints is a redundant manipulator. Also, a manipulator whose end-effector can accept aspatialposeisaredundant manipulator ifithas morethan sixindependently driven joints. For example, the manipulator shown in Fig. 1.1 has two 7-DOF arms mounted on a torso with three degrees of freedom (DOFs). This provides 10 DOFs for each arm. Since the end-effector of each arm can have a spatial motion with six DOFs, the arms are redundant.
標簽： Autonomous Modeling Planning Robots Path
上傳時間： 2020-06-10
上傳用戶：shancjb
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propa- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.
標簽： Bishop-Pattern-Recognition-and-Ma chine-Learning
上傳時間： 2020-06-10
上傳用戶：shancjb
Artificial Intelligence (AI) has undoubtedly been one of the most important buz- zwords over the past years. The goal in AI is to design algorithms that transform com- puters into “intelligent” agents. By intelligence here we do not necessarily mean an extraordinary level of smartness shown by superhuman; it rather often involves very basic problems that humans solve very frequently in their day-to-day life. This can be as simple as recognizing faces in an image, driving a car, playing a board game, or reading (and understanding) an article in a newspaper. The intelligent behaviour ex- hibited by humans when “reading” is one of the main goals for a subfield of AI called Natural Language Processing (NLP). Natural language 1 is one of the most complex tools used by humans for a wide range of reasons, for instance to communicate with others, to express thoughts, feelings and ideas, to ask questions, or to give instruc- tions. Therefore, it is crucial for computers to possess the ability to use the same tool in order to effectively interact with humans.
標簽： Embeddings Processing Language Natural in
上傳時間： 2020-06-10
上傳用戶：shancjb
Current field forecast verification measures are inadequate, primarily because they compress the comparison between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to analysis and contemporaneous forecast fields prove to be an insightful approach to verification problems. DWTs allow both filtering and compact physically interpretable partitioning of fields. These techniques are used to reduce or eliminate noise in the verification process and develop multivariate measures of field forecasting performance that are shown to improve upon existing verification procedures.
標簽： field forecast verification
上傳時間： 2020-07-22
上傳用戶：
This edition of Digital Image Processing is a major revision of the book. As in the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992, 2002, and 2008 editions by Gonzalez and Woods, this sixth-generation edition was prepared with students and instructors in mind. The principal objectives of the book continue to be to provide an introduction to basic concepts and methodologies applicable to digital image processing, and to develop a foundation that can be used as the basis for further study and research in this field. To achieve these objectives, we focused again on material that we believe is fundamental and whose scope of application is not limited to the solution of specialized problems. The mathematical complexity of the book remains at a level well within the grasp of college seniors and first-year graduate students who have introductory preparation in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. The book website provides tutorials to support readers needing a review of this background material
標簽： Processing Digital Image
上傳時間： 2021-02-20
上傳用戶：
An Arduino core for the ATmega328, ATmega168, ATmega88, ATmega48 and ATmega8, all running a [custom version of Optiboot for increased functionality](#write-to-own-flash). This core requires at least Arduino IDE v1.6.2, where v1.8.5+ is recommended. <br/> **This core gives you two extra IO pins if you're using the internal oscillator!** PB6 and PB7 is mapped to [Arduino pin 20 and 21](#pinout).<br/> If you're into "generic" AVR programming, I'm happy to tell you that all relevant keywords are being highlighted by the IDE through a separate keywords file. Make sure to test the [example files](https://github.com/MCUdude/MiniCore/tree/master/avr/libraries/AVR_examples/examples) (File > Examples > AVR C code examples). Try writing a register name, <i>DDRB</i> for instance, and see for yourself!
標簽： MiniCore
上傳時間： 2021-02-22
上傳用戶：
%this is an example demonstrating the Radial Basis Function %if you select a RBF that supports it (Gausian, or 1st or 3rd order %polyharmonic spline), this also calculates a line integral between two %points.
上傳時間： 2021-07-02
上傳用戶：19800358905
This programming manual provides information for application and system-level softwaredevelopers. It gives a full description of the STM32F3 and STM32F4 Series Cortex?-M4processor programming model, instruction set and core peripherals.
標簽： stm32f7
上傳時間： 2021-12-02
上傳用戶：
軟件開發人員必備工具書，，目錄如下Welcome to Software Construction [1]1.1 What Is Software Construction?1.2 Why Is Software Construction Important?1.3 How to Read This Book......7.1 Valid Reasons to Create a Routine7.2 Design at the Routine Level7.3 Good Routine Names7.4 How Long Can a Routine Be?7.5 How to Use Routine Parameters7.6 Special Considerations in the Use of Functions7.7 Macro Routines and Inline RoutinesDefensive Programming [5.6 + new material]8.1 Protecting Your Program From Invalid Inputs8.2 Assertions8.3 Error Handling Techniques8.4 Exceptions8.5 Barricade Your Program to Contain the Damage Caused by Errors8.6 Debugging Aids8.7 Determining How Much Defensive Programming to Leave in Production Code8.8 Being Defensive About Defensive ProgrammingThe Pseudocode Programming Process [4+new material]9.1 Summary of Steps in Building Classes and Routines9.2 Pseudocode for Pros9.3 Constructing Routines Using the PPP9.4 Alternatives to the PPP......
上傳時間： 2021-12-08
上傳用戶：20125101110
This texts contemporary approach focuses on the concepts of linear control systems, rather than computational mechanics. Straightforward coverage includes an integrated treatment of both classical and modern control system methods. The text emphasizes design with discussions of problem formulation, design criteria, physical constraints, several design methods, and implementation of compensators.Discussions of topics not found in other texts--such as pole placement, model matching and robust tracking--add to the texts cutting-edge presentation. Students will appreciate the applications and discussions of practical aspects, including the leading problem in developing block diagrams, noise, disturbances, and plant perturbations. State feedback and state estimators are designed using state variable equations and transfer functions, offering a comparison of the two approaches. The incorporation of MATLAB throughout the text helps students to avoid time-consuming computation and concentrate on control system design and analysis
標簽： 控制系統
上傳時間： 2021-12-15
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