نتایج جستجو برای: slam

تعداد نتایج: 3598  

Journal: :Sensors 2019

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Journal: :The International Journal of Robotics Research 2011

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Journal: :SoundEffects - An Interdisciplinary Journal of Sound and Sound Experience 2017

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Journal: :Automatica 2015
Heng Wang Shoudong Huang Kasra Khosoussi Udo Frese Gamini Dissanayake Bingbing Liu

The main contribution of this paper is the dimensionality reduction for multiple-step 2D point feature based Simultaneous Localization and Mapping (SLAM), which is an extension of our previous work on one-step SLAM (Wang, Huang, Frese & Dissanayake 2013). It has been proved that SLAM with multiple robot poses and a number of point feature positions as variables is equivalent to an optimization ...

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2004
Thomas Ball Byron Cook Satyaki Das Sriram K. Rajamani

ion Thomas Ball†, Byron Cook†, Satyaki Das, and Sriram K. Rajamani† † Microsoft Corporation ? Stanford University Abstract. Predicate abstraction is an automatic technique that can be used to find abstract models of large or infinite-state systems. In tools like Slam, where predicate abstraction is applied to software model checking, a number of heuristic approximations must be used to improve ...

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2017
María Elena López Guillén Sergio García Rafael Barea Luis Miguel Bergasa Eduardo J. Molinos Roberto Arroyo Eduardo Romera Samuel Pardo

One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The prop...

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Journal: :I. J. Robotics Res. 2007
Chieh-Chih Wang Charles E. Thorpe Sebastian Thrun Martial Hebert Hugh F. Durrant-Whyte

LOCALIZATION, mapping and moving object tracking serve as the basis for scene understanding, which is a key prerequisite for making a robot truly autonomous. Simultaneous localization, mapping and moving object tracking (SLAMMOT) involves not only simultaneous localization and mapping (SLAM) in dynamic environments but also detecting and tracking these dynamic objects. It is believed by many th...

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2016
Na Feng Yuxiu Liu Jianzhong Wang Weiwei Xu Tiansong Li Tiecheng Wang Lei Wang Yicong Yu Hualei Wang Yongkun Zhao Songtao Yang Yuwei Gao Guixue Hu Xianzhu Xia

BACKGROUND In 2008, an outbreak of canine distemper virus (CDV) infection in monkeys was reported in China. We isolated CDV strain (subsequently named Monkey-BJ01-DV) from lung tissue obtained from a rhesus monkey that died in this outbreak. We evaluated the ability of this virus on Vero cells expressing SLAM receptors from dog, monkey and human origin, and analyzed the H gene of Monkey-BJ01-DV...

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2013
Edmundo Guerra Rodrigo Munguia Yolanda Bolea Antoni Grau

Simultaneous Location and Mapping (SLAM) is a key problem to solve in order to build truly autonomous mobile robots. SLAM with a unique camera, or monocular SLAM, is probably one of the most complex SLAM variants, based entirely on a bearing-only sensor working over six DOF. The monocular SLAM method developed in this work is based on the Delayed Inverse-Depth (DI-D) Feature Initialization, wit...

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Journal: :Proceedings of the National Academy of Sciences of the United States of America 2007
Qingrong Yan Vladimir N Malashkevich Alexander Fedorov Elena Fedorov Erhu Cao Jeffrey W Lary James L Cole Stanley G Nathenson Steven C Almo

The signaling lymphocyte activation molecule (SLAM) family includes homophilic and heterophilic receptors that modulate both adaptive and innate immune responses. These receptors share a common ectodomain organization: a membrane-proximal immunoglobulin constant domain and a membrane-distal immunoglobulin variable domain that is responsible for ligand recognition. CD84 is a homophilic family me...

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  • " +i+ "
    • "; pgn_html+=pgn_li; } document.getElementById("pgn-ul").innerHTML=pgn_html var pgn_links = document.querySelectorAll('.mypgn'); pgn_links.forEach(function(pgn_link) { pgn_link.addEventListener('click', paginate) }) } function post_and_fetch(data,url) { showLoading() xhr = new XMLHttpRequest(); xhr.open('POST', url, true); xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8'); xhr.onreadystatechange = function() { if (xhr.readyState === 4 && xhr.status === 200) { var resp = xhr.responseText; resp_json=JSON.parse(resp) resp_place = document.getElementById("search_result_div") resp_place.innerHTML = resp_json['results'] search_meta = resp_json['meta'] update_search_meta(search_meta) update_pagination() hideLoading() } }; xhr.send(JSON.stringify(data)); } function unfilter() { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":"unfilter", "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } function deactivate_all_bars(){ var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(bar) { bar.dataset.active = false bar.style = "stroke:#71a3c5;" }) } year_chart.on("created", function() { var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(check) { check.addEventListener('click', checkIndex); }) }); function checkIndex(event) { var yrchart = document.querySelectorAll('.ct-bar'); var year_bar = event.target if (year_bar.dataset.active == "true") { unfilter_res = unfilter() year_bar.dataset.active = false year_bar.style = "stroke:#1d2b3699;" } else { deactivate_all_bars() year_bar.dataset.active = true year_bar.style = "stroke:#e56f6f;" filter_year = chart_data['labels'][Array.from(yrchart).indexOf(year_bar)] url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":filter_year, "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } } function showLoading() { document.getElementById("loading").style.display = "block"; setTimeout(hideLoading, 10000); // 10 seconds } function hideLoading() { document.getElementById("loading").style.display = "none"; } -->