Patents by Inventor Bhanu Kiran Reddy Palla
Bhanu Kiran Reddy Palla has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240013124Abstract: A predictive engine obtains as inputs a set of optimization criteria and a time horizon selection input and applies those inputs to a time horizon model in a variable time horizon prediction engine. A user interface is generated that provides actuatable elements that can be actuated in order to access different time horizon models in the variable time horizon prediction engine. Operational parameters can be adjusted so that the variable time horizon prediction engine provides an output indicative of a control signal that can be used to improve operation of the agricultural system over the selected time horizon.Type: ApplicationFiled: July 8, 2022Publication date: January 11, 2024Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA
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Patent number: 11864483Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: GrantFiled: October 9, 2020Date of Patent: January 9, 2024Assignee: Deere & CompanyInventors: Nathan R. Vandike, Bhanu Kiran Reddy Palla, Noel W. Anderson, Stephen R. Corban
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Patent number: 11849671Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: GrantFiled: October 9, 2020Date of Patent: December 26, 2023Assignee: Deere & CompanyInventors: Nathan R. Vandike, Bhanu Kiran Reddy Palla, Noel W. Anderson, Federico Pardina-Malbran
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Patent number: 11849672Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: GrantFiled: October 9, 2020Date of Patent: December 26, 2023Assignee: Deere & CompanyInventors: Nathan R Vandike, Bhanu Kiran Reddy Palla, Corwin M. Puryk
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Patent number: 11844311Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: GrantFiled: October 9, 2020Date of Patent: December 19, 2023Assignee: Deere & CompanyInventors: Nathan R. Vandike, Bhanu Kiran Reddy Palla, Noel W. Anderson
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Patent number: 11845449Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: GrantFiled: October 9, 2020Date of Patent: December 19, 2023Assignee: Deere & CompanyInventors: Nathan R Vandike, Bhanu Kiran Reddy Palla
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Publication number: 20230397532Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: August 8, 2023Publication date: December 14, 2023Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA, Noel W. ANDERSON, Federico PARDINA-MALBRAN
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Publication number: 20230393577Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: August 10, 2023Publication date: December 7, 2023Inventors: Nathan R. Vandike, Bhanu Kiran Reddy Palla, Federico Pardina-Malbran, Matthew T. Wold, Cody W. Best, Noel W. Anderson
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Publication number: 20230380346Abstract: A priori georeferenced vegetative index data is obtained for a worksite, along with field data that is collected by a sensor on a work machine that is performing an operation at the worksite. A predictive model is generated, while the machine is performing the operation, based on the georeferenced vegetative index data and the field data. A model quality metric is generated for the predictive model and is used to determine whether the predictive model is a qualified predicative model. If so, a control system controls a subsystem of the work machine, using the qualified predictive model, and a position of the work machine, to perform the operation.Type: ApplicationFiled: August 8, 2023Publication date: November 30, 2023Inventors: Noel W. ANDERSON, Nathan R. VANDIKE, Federico PARDINA-MALBRAN, Bhanu Kiran Reddy PALLA
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Patent number: 11829112Abstract: A priori geo-referenced data is obtained for a worksite, along with field data that is collected by a sensor on a work machine that is performing an operation at the worksite. A predictive model is generated, while the machine is performing the operation, based on the geo-referenced data and the field data. A model quality metric is generated for the predictive model and is used to determine whether the predictive model is a qualified predicative model. If so, a control system controls a subsystem of the work machine, using the qualified predictive model, and a position of the work machine, to perform the operation.Type: GrantFiled: March 17, 2023Date of Patent: November 28, 2023Assignee: Deere & CompanyInventors: Bhanu Kiran Reddy Palla, Nathan R. Vandike, Federico Pardina-Malbran, Noel W. Anderson, Michael A. Waldo
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Patent number: 11825768Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: GrantFiled: October 9, 2020Date of Patent: November 28, 2023Assignee: Deere & CompanyInventors: Nathan R Vandike, Bhanu Kiran Reddy Palla, Nathan E. Krehbiel, Duane M. Bomleny
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Patent number: 11821176Abstract: A mobile machine includes a propulsion subsystem that propels the mobile machine across an operational environment. The mobile machine also includes machine monitoring logic that receives a sensor signal indicative of a value of a sensed machine variable and operator monitoring logic that receives an operator sensor signal indicative of a value of a sensed operator variable. The mobile machine also includes performance index generator logic that receives the sensed machine variable and the sensed operator value and generates a performance index based on the sensed machine variable and the sensed operator value. The mobile machine also includes optimization system that accesses historic circumstantial data and receives the performance index and generates an optimization signal based on the performance index, and the historic circumstantial data and control signal generator logic that generates a control signal based on the optimization signal to perform a machine operation.Type: GrantFiled: August 30, 2019Date of Patent: November 21, 2023Assignee: Deere & CompanyInventors: Bradley Lan, Wentao Yu, Bhanu Kiran Reddy Palla, Volker Fuchs
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Publication number: 20230345874Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: June 21, 2023Publication date: November 2, 2023Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA, Noel W. ANDERSON
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Publication number: 20230337566Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: June 21, 2023Publication date: October 26, 2023Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA, Noel W. ANDERSON, Stephen R. CORBAN
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Publication number: 20230337582Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: June 21, 2023Publication date: October 26, 2023Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA, Nathan E. KREHBIEL, Duane M. BOMLENY
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Publication number: 20230334853Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: June 20, 2023Publication date: October 19, 2023Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA, Noel W. ANDERSON
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Publication number: 20230320254Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: June 7, 2023Publication date: October 12, 2023Inventors: Nathan R. VANDIKE, Bhanu Kiran Reddy PALLA, Nathan GREUEL
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Publication number: 20230320259Abstract: An information map is obtained by an agricultural system. The information map maps values of a characteristic at different geographic locations in a worksite. An in-situ sensor detects nutrient values as a mobile material application machine operates at the worksite. A predictive map generator generates a predictive map that maps predictive nutrient values at different geographic locations in the worksite based on a relationship between values of the characteristic in the information map and nutrient values detected by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: April 8, 2022Publication date: October 12, 2023Inventors: Nathan R. Vandike, Bhanu Kiran Reddy Palla, Federico Pardina-Malbran, Travis J. Auderer, Kevin A. Thelen, Noel W. Anderson
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Publication number: 20230324910Abstract: An information map is obtained by an agricultural system. The information map maps values of a characteristic at different geographic locations in a worksite. An in-situ sensor detects material consumption values as a mobile material application machine operates at the worksite. A predictive map generator generates a predictive map that maps predictive material consumption values at different geographic locations in the worksite based on a relationship between values of the characteristic in the information map and material consumption values detected by the in-situ sensor. The predictive map can be output and used in automated machine control.Type: ApplicationFiled: April 8, 2022Publication date: October 12, 2023Inventors: Nathan R. Vandike, Bhanu Kiran Reddy Palla, Federico Pardina-Malbran, Noel W. Anderson
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Patent number: 11778945Abstract: A priori georeferenced vegetative index data is obtained for a worksite, along with field data that is collected by a sensor on a work machine that is performing an operation at the worksite. A predictive model is generated, while the machine is performing the operation, based on the georeferenced vegetative index data and the field data. A model quality metric is generated for the predictive model and is used to determine whether the predictive model is a qualified predicative model. If so, a control system controls a subsystem of the work machine, using the qualified predictive model, and a position of the work machine, to perform the operation.Type: GrantFiled: April 10, 2019Date of Patent: October 10, 2023Assignee: Deere & CompanyInventors: Noel W. Anderson, Nathan R. Vandike, Federico Pardina-Malbran, Bhanu Kiran Reddy Palla