عنوان: آموزش ساخت کوادکوپتر

نویسنده: Jean-Louis Naudin

ناشر: وبلاگ شخصی Jean-Louis Naudin

زبان: انگلیسی

تعداد صفحهی فایل پیدیاف: ۱۱ صفحه (رنگی)

حجم: ۵٫۲۷ مگابایت

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برای مشاهده ی کوادکوپتری که نویسنده ی این جزوه ساخته است، ویدئوی زیر را مشاهده نمایید.

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جعبه ابزار آموزش رباتیک در متلب چیست؟

جعبه ابزار آموزش رباتیک در متلب ( ARTE : A ROBOTICS TOOLBOX FOR EDUCATION ) درواقع یک جعبه ابزار ( Toolbox ) برای نرم افزار برنامه نویسی متلب ( MATLAB ) است که در آن روی منیپولاتورهای سری و موازی تمرکز شده است.

ویژگی های اصلی جعبه ابزار آموزش رباتیک در متلب

۱- شبیه سازی انواع ربات در محیط متلب

۲- قانون دناویت هارتنبرگ در متلب

۳- ربات های مختلف به صورت سه بعدی

۴- سینماتیک ربات در متلب

۵- دینامیک ربات در متلب

۶- رابط کاربری مربوط به ربات در متلب

۷- ارتباط متلب با زبان ABB RAPID

۸- کنترل یک ربات واقعی با متلب

۹- تعریف ربات در متلب

فیلم های زیر بخشی از کارکردهای این نرم افزار را نمایش می دهند.

برای مشاهده ی صفحه ی این نرم افزار در یوتیوب اینجا (+) کلیک نمایین.

منبع: تارنمای نرم افزار ARTE (ترجمه با اندکی تغییرات است.)

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عنوان کتاب: Structure from Motion using the Extended Kalman Filter

نویسندگان: Civera, Javier, Davison, Andrew J., Martínez Montiel, José María

سال انتشار: ۲۰۱۲

زبان: انگلیسی

تعداد صفحات فایل پی دی اف: ۱۷۹ صفحه (رنگی)

حجم فایل: ۸٫۵۱ مگابایت

منبع: Library Genesis

توضیح: این هفتاد و پنجمین کتاب از «مجموعهی رباتیک پیشرفتهی انتشارات اسپرینگر» است. (STAR 75)

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کاربر گرامی برای مشاهده پیوند دریافت فایل باید وارد سایت شده و دارای عضویت ویژه باشید.

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معرفی کوتاه

The fully automated estimation of the 6 degrees of freedom camera motion and the imaged 3D scenario using as the only input the pictures taken by the camera has been a long term aim in the computer vision community. The associated line of research has been known as Structure from Motion (SfM). An intense research effort during the latest decades has produced spectacular advances; the topic has reached a consistent state of maturity and most of its aspects are well known nowadays. 3D vision has immediate applications in many and diverse fields like robotics, videogames and augmented reality; and technological transfer is starting to be a reality.

This book describes one of the first systems for sparse point-based 3D reconstruction and egomotion estimation from an image sequence; able to run in real-time at video frame rate and assuming quite weak prior knowledge about camera calibration, motion or scene. Its chapters unify the current perspectives of the robotics and computer vision communities on the 3D vision topic: As usual in robotics sensing, the explicit estimation and propagation of the uncertainty hold a central role in the sequential video processing and is shown to boost the efficiency and performance of the 3D estimation. On the other hand, some of the most relevant topics discussed in SfM by the computer vision scientists are addressed under this probabilistic filtering scheme; namely projective models, spurious rejection, model selection and self-calibration.

محتویات کتاب

Front Matter….Pages 1-13
Introduction….Pages 1-12
Points at Infinity: Mosaics Using the Extended Kalman Filter….Pages 13-32
Inverse Depth Parametrization….Pages 33-63
۱-Point RANSAC….Pages 65-97
Degenerate Camera Motions and Model Selection….Pages 99-110
Self-calibration….Pages 111-122
Conclusions….Pages 123-125
Back Matter….Pages 1-43

مقدمه

The book you have in your hands is the result of the joint research of the authors from 2006 to 2009, that led to Javier Civera’s PhD thesis. The contributions on it were first published in several inteational conferences and jouals; specifically and in chronological order [Montiel et al. 2006, Civera et al. 2007a, Civera et al. 2007b, Civera et al. 2008a, Civera et al. 2008b, Civera et al. 2009b, Civera et al. 2009a, Civera et al. 2009c, Civera et al. 2010]. This book provides a unified view of the research spread on those papers, presenting a complete and robust system aimed to sequential 3D vision in real-time.

Along the years, many people have contributed in one or another maer to the results presented here. First of all, we are very grateful to our coauthors in the topics related with this book O´ scar G. Grasa, Diana R. Bueno and Juan A. Magallo´n. Gabe Sibley and Joan Sol`a reviewed the first version of the PhD thesis manuscript. The jury of Javier Civera’s PhD defence;Wolfram Burgard, J. D. Tard´os, Patric Jensfelt, Miguel A´ ngel Salichs and V´ıctor Mun˜oz, contributed to this final version with very insightful Idea and aotations. The expert eyes of Antonio Agudo, O´ scar G.

Grasa, Lina Paz y Pedro Pini´es also reviewed the final version of this book and contibuted to polish some discussions and to find the latest and more difficult bugs. The authors are also extremely grateful to their respective research groups: the Robot Vision Group at Imperial College in London and the Robotics, Perception and Real-Time Group in the I3A (Arag´on Institute on EngineeringResearch) in the University of Zaragoza in Spain. Hundreds of relevant conversations, the stimulating research atmosphere and the dedication at both groups are fertile breeding grounds that have played an essential role in our research. An exhaustive list of names would be an unfeasible task, but still we would like to express our gratitude to some of our colleagues
for very interesting discussions: Jos´e Neira, Pedro Pini´es, Lina Paz, Rub´en Mart´ınez-Cant´ın, Luis Montesano, Alejandro Mosteo, Ana Cristina Murillo, I˜naki Ra˜no, Antonio Agudo, Margarita Chli, Hauke Strasdat, Ian Reid, Brian Williams and Cyrill Stachniss. Last but not least, we are in debt with our respective families, for their constant support.

The research results in this book were financially supported by the following sources: The Spanish Goverment research grants DPI2003-07986, DPI2006-13578, DPI2009-07130 and PR2007-0427; regional grant DGA(CONAI+D)-CAI IT12-06; the European Union projects RAWSEEDS FP6-045144 and RoboEarth FP7-248942; and A. J. Davison’s ERC Starting Grant 210346.

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