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            	{"first" : "Matthias A.",	"last" : "Müller"},
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         "intraHash" : "9478082d973e7c9ac16788830bf88ffe",
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         "label" : "Trajektorienplanung mittels modellprädiktiver Vorsteuerung eines FDM-Druckkopfes",
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         "description" : "",
         "date" : "2019-06-05 15:13:46",
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         "booktitle": "26. Stuttgarter Kunststoffkolloquium","publisher":"IKT, Universität Stuttgart",
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         "url": "", 
         
         "author": [ 
            "Frederik Wulle","Wolfgang Bubeck","Anja Elser","Martin Wolf","Alexander Verl"
         ],
         "authors": [
         	
            	{"first" : "Frederik",	"last" : "Wulle"},
            	{"first" : "Wolfgang",	"last" : "Bubeck"},
            	{"first" : "Anja",	"last" : "Elser"},
            	{"first" : "Martin",	"last" : "Wolf"},
            	{"first" : "Alexander",	"last" : "Verl"}
         ],
         "pages": "83-88","abstract": "Das dynamische Verhalten von Kunststoffextrudern wird in der Trajektorienplanung bei der Additiven Fertigung kaum berücksichtigt. Dies verursacht Prozess- und Bauteilqualitätsminderungen, die vor allem in den Anfahr- und Endphasen beim Ablegen von Raupen sichtbar werden. Durch eine modellprädiktive Vorsteuerung auf Basis einer Dynamikmodellierung des Kunstoffes im Extruder kann der Volumenstrom jedoch geregelt werden.\r\nDiese Trajektorienplanung läuft auf der CNC in Echtzeit und beeinflusst zusätzlich die Trajektorie des Druckkopfs.\r\nAnhand eines Beispiels wird ein Lösungsvorschlag für eine Modellierung und Implementierung erläutert.",
         "venue" : "Stuttgart",
         
         "isbn" : "978-3-9818681-1-1",
         
         "language" : "deutsch",
         
         "eventdate" : "28.03.2019",
         
         "bibtexKey": "wulle2019trajektorienplanung"

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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2c749188fdea5a8a7b1a8be98f7af02d7/geoinst",         
         "tags" : [
            "UAV","control","detection","digital","elevation","excessive","green","index","mapping","model","patch","red","site-specific","spraying","vegetation","weed"
         ],
         
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         "label" : "Multi-Temporal Site-Specific Weed Control of Cirsium arvense (L.) Scop. and Rumex crispus L. in Maize and Sugar Beet Using Unmanned Aerial Vehicle Based Mapping",
         "user" : "geoinst",
         "description" : "",
         "date" : "2018-12-07 13:05:48",
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         "journal": "Agriculture",
         "year": "2018", 
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         "author": [ 
            "Robin Mink","Avishek Dutta","Gerassimos G. Peteinatos","Markus Sökefeld","Johannes Joachim Engels","Michael Hahn","Roland Gerhards"
         ],
         "authors": [
         	
            	{"first" : "Robin",	"last" : "Mink"},
            	{"first" : "Avishek",	"last" : "Dutta"},
            	{"first" : "Gerassimos G.",	"last" : "Peteinatos"},
            	{"first" : "Markus",	"last" : "Sökefeld"},
            	{"first" : "Johannes Joachim",	"last" : "Engels"},
            	{"first" : "Michael",	"last" : "Hahn"},
            	{"first" : "Roland",	"last" : "Gerhards"}
         ],
         "volume": "8","number": "5","pages": "1-14","abstract": "Sensor-based weed mapping in arable fields is a key element for site-specific herbicide management strategies. In this study, we investigated the generation of application maps based on Unmanned Aerial Vehicle imagery and present a site-specific herbicide application using those maps. Field trials for site-specific herbicide applications and multi-temporal image flights were carried out in maize ( Zea mays L.) and sugar beet ( Beta vulgaris L.) in southern Germany. Real-time kinematic Global Positioning System precision planting information provided the input for determining plant rows in the geocoded aerial images. Vegetation indices combined with generated plant height data were used to detect the patches containing creeping thistle ( Cirsium arvense (L.) Scop.) and curled dock ( Rumex crispus L.). The computed weed maps showed the presence or absence of the aforementioned weeds on the fields, clustered to 9 m × 9 m grid cells. The precision of the correct classification varied from 96% in maize to 80% in the last sugar beet treatment. The computational underestimation of manual mapped C. arvense and R. cripus patches varied from 1% to 10% respectively. Overall, the developed algorithm performed well, identifying tall perennial weeds for the computation of large-scale herbicide application maps.",
         "bibtexKey": "Engels2018a"

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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/26682c1eea696d736e36e234fee59f969/isyspub",         
         "tags" : [
            "BHA","Festo","ISYS","control","model","redundant","robotics"
         ],
         
         "intraHash" : "6682c1eea696d736e36e234fee59f969",
         "interHash" : "347ecdc69e762c7b3899e75edf17c32a",
         "label" : "A Variable Curvature Modeling Approach for Kinematic Control of Continuum Manipulators",
         "user" : "isyspub",
         "description" : "",
         "date" : "2017-11-28 18:08:48",
         "changeDate" : "2017-11-28 17:08:48",
         "count" : 2,
         "pub-type": "inproceedings",
         "booktitle": "American Control Conference (ACC)","address":"Washington, DC, USA",
         "year": "2013", 
         "url": "", 
         
         "author": [ 
            "Tobias Mahl","Annika Mayer","Alexander Hildebrandt","Oliver Sawodny"
         ],
         "authors": [
         	
            	{"first" : "Tobias",	"last" : "Mahl"},
            	{"first" : "Annika",	"last" : "Mayer"},
            	{"first" : "Alexander",	"last" : "Hildebrandt"},
            	{"first" : "Oliver",	"last" : "Sawodny"}
         ],
         "pages": "4952--4957",
         "isys_group" : "Mechatronik,\nAntriebssysteme",
         
         "file" : "Mahl2013a_ACC_Variable_Curvature_Kinematic_BHA.pdf:..\\\\pdfs\\\\Mahl2013a_ACC_Variable_Curvature_Kinematic_BHA.pdf:PDF;Mahl2013a_ACC_Variable_Curvature_Kinematic_BHA_official.pdf:..\\\\pdfs\\\\Mahl2013a_ACC_Variable_Curvature_Kinematic_BHA_official.pdf:PDF",
         
         "isys_authors" : "tmahl, amayer",
         
         "bibtexKey": "Mahl2013a"

      }
	  
   ]
}
