無線通信的各種運動模型。適用于移動通信、無線傳感器網絡等領域。 包括：Random walk、random waypoint、random direction、boundless simulation area、 gauss-markov等運動模型 - Probabilistic random walk
標簽： random simulation direction boundless
上傳時間： 2014-11-12
上傳用戶：libinxny
This paper presents a visual based localization mechanism for a legged robot. Our proposal, fundamented on a Probabilistic approach, uses a precompiled topological map where natural landmarks like doors or ceiling lights are recognized by the robot using its on-board camera. Experiments have been conducted using the AIBO Sony robotic dog showing that it is able to deal with noisy sensors like vision and to approximate world models representing indoor ofce environments. The two major contributions of this work are the use of this technique in legged robots, and the use of an active camera as the main sensor
標簽： localization mechanism presents proposal
上傳時間： 2016-11-04
上傳用戶：dianxin61
卡耐基.梅隆大學的牛發寫的關于孤立點和數據清洗的文章，全英文，2003年完成，Probabilistic Noise Identification and Data Cleaning，Real world data is never as perfect as we would like it to be and can often suffer from corruptions that may impact interpretations of the data, models created from the data, and decisions made based on the data. One approach to this problem is to identify and remove records that contain corruptions. Unfortunately, if only certain fields in a record have been corrupted then usable, uncorrupted data will be lost. In this paper we present LENS, an approach for identifying corrupted fields and using the remaining noncorrupted fields for subsequent modeling and analysis.
上傳時間： 2017-08-29
上傳用戶：thinode
斯坦福大牛作品，機器人入門必讀書之一，學習后力量無窮
標簽： Probabilistic Robotics pdf
上傳時間： 2017-11-29
上傳用戶：BITLQX
The main aim of this book is to present a unified, systematic description of basic and advanced problems, methods and algorithms of the modern con- trol theory considered as a foundation for the design of computer control and management systems. The scope of the book differs considerably from the topics of classical traditional control theory mainly oriented to the needs of automatic control of technical devices and technological proc- esses. Taking into account a variety of new applications, the book presents a compact and uniform description containing traditional analysis and op- timization problems for control systems as well as control problems with non-Probabilistic models of uncertainty, problems of learning, intelligent, knowledge-based and operation systems – important for applications in the control of manufacturing processes, in the project management and in the control of computer systems.
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
