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10.3390/s17061422 http://scihub22266oqcxt.onion/10.3390/s17061422 C5492843!5492843!28629141     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sensors+(Basel) 2017 ; 17 (6): ä Nephropedia Template TP {{tp|p=28629141|t=2017. Graph-Based Cooperative Localization Using Symmetric Measurement Equations |pdf=|usr=}}{{28629141}} gab.com Text Graph-Based Cooperative Localization Using Symmetric Measurement Equations JO: Sensors (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=28629141 #FOAvip Precise localization is a key requirement for the success of highly assisted or autonomous vehicles. The diminishing cost of hardware has resulted in a proliferation of the number of sensors in the environment. Cooperative localization (CL) presents itself as a feasible and effective solution for localizing the ego-vehicle and its neighboring vehicles. However, one of the major challenges to fully realize the effective use of infrastructure sensors for jointly estimating the state of a vehicle in cooperative vehicle-infrastructure localization is an effective data association. In this paper, we propose a method which implements symmetric measurement equations within factor graphs in order to overcome the data association challenge with a reduced bandwidth overhead. Simulated results demonstrate the benefits of the proposed approach in comparison with our previously proposed approach of topology factors. Twit Text FOAVip Graph-Based Cooperative Localization Using Symmetric Measurement Equations ????Sensors (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=28629141 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28629141 #FOAvip English Wikipedia <ref>{{Cite pmid|28629141}}</ref> Graph-Based Cooperative Localization Using Symmetric Measurement Equations #MMPMID28629141 Gulati D; Zhang F; Clarke D; Knoll A Sensors (Basel) 2017[Jun]; 17 (6): ä PMID28629141show ga Precise localization is a key requirement for the success of highly assisted or autonomous vehicles. The diminishing cost of hardware has resulted in a proliferation of the number of sensors in the environment. Cooperative localization (CL) presents itself as a feasible and effective solution for localizing the ego-vehicle and its neighboring vehicles. However, one of the major challenges to fully realize the effective use of infrastructure sensors for jointly estimating the state of a vehicle in cooperative vehicle-infrastructure localization is an effective data association. In this paper, we propose a method which implements symmetric measurement equations within factor graphs in order to overcome the data association challenge with a reduced bandwidth overhead. Simulated results demonstrate the benefits of the proposed approach in comparison with our previously proposed approach of topology factors. äGraph-Based Cooperative Localization Using Symmetric Measurement Equat(epmc).pdf DeepDyve Pubget Overpricing