Patents by Inventor Eran Asa
Eran Asa 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).
-
Publication number: 20240096014Abstract: A computer implemented method of creating data for a host vehicle simulation, comprising: in each of a plurality of iterations of a host vehicle simulation using at least one processor for: obtaining from an environment simulation engine a semantic-data dataset representing a plurality of scene objects in a geographical area, each one of the plurality of scene objects comprises at least object location coordinates and a plurality of values of semantically described parameters; creating a 3D visual realistic scene emulating the geographical area according to the dataset; applying at least one noise pattern associated with at least one sensor of a vehicle simulated by the host vehicle simulation engine on the virtual 3D visual realistic scene to create sensory ranging data simulation of the geographical area; converting the sensory ranging data simulation to an enhanced dataset emulating the geographical area, the enhanced dataset comprises a plurality of enhanced scene objects.Type: ApplicationFiled: November 24, 2023Publication date: March 21, 2024Applicant: Cognata Ltd.Inventors: Dan ATSMON, Guy TSAFRIR, Eran ASA
-
Publication number: 20230306680Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.Type: ApplicationFiled: May 29, 2023Publication date: September 28, 2023Applicant: Cognata Ltd.Inventors: Dan ATSMON, Eran ASA, Ehud SPIEGEL
-
Patent number: 11694388Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.Type: GrantFiled: July 23, 2021Date of Patent: July 4, 2023Assignee: Cognata Ltd.Inventors: Dan Atsmon, Eran Asa, Ehud Spiegel
-
Publication number: 20220188579Abstract: A method for training a model for generating simulation data for training an autonomous driving agent, comprising: analyzing real data, collected from a driving environment, to identify a plurality of environment classes, a plurality of moving agent classes, and a plurality of movement pattern classes; generating a training environment, according to one environment class; and in at least one training iteration: generating, by a simulation generation model, a simulated driving environment according to the training environment and according to a plurality of generated training agents, each associated with one of the plurality of agent classes and one of the plurality of movement pattern classes; collecting simulated driving data from the simulated environment; and modifying at least one model parameter of the simulation generation model to minimize a difference between a simulation statistical fingerprint, computed using the simulated driving data, and a real statistical fingerprint, computed using the real datType: ApplicationFiled: March 7, 2022Publication date: June 16, 2022Applicant: Cognata Ltd.Inventors: Dan ATSMON, Eran ASA, Ehud SPIEGEL
-
Patent number: 11270165Abstract: A method for training a model for generating simulation data for training an autonomous driving agent, comprising: analyzing real data, collected from a driving environment, to identify a plurality of environment classes, a plurality of moving agent classes, and a plurality of movement pattern classes; generating a training environment, according to one environment class; and in at least one training iteration: generating, by a simulation generation model, a simulated driving environment according to the training environment and according to a plurality of generated training agents, each associated with one of the plurality of agent classes and one of the plurality of movement pattern classes; collecting simulated driving data from the simulated environment; and modifying at least one model parameter of the simulation generation model to minimize a difference between a simulation statistical fingerprint, computed using the simulated driving data, and a real statistical fingerprint, computed using the real datType: GrantFiled: October 15, 2019Date of Patent: March 8, 2022Assignee: Cognata Ltd.Inventors: Dan Atsmon, Eran Asa, Ehud Spiegel
-
Publication number: 20210350185Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.Type: ApplicationFiled: July 23, 2021Publication date: November 11, 2021Applicant: Cognata Ltd.Inventors: Dan ATSMON, Eran ASA, Ehud SPIEGEL
-
Publication number: 20210312244Abstract: A method for training a model for generating simulation data for training an autonomous driving agent, comprising: analyzing real data, collected from a driving environment, to identify a plurality of environment classes, a plurality of moving agent classes, and a plurality of movement pattern classes; generating a training environment, according to one environment class; and in at least one training iteration: generating, by a simulation generation model, a simulated driving environment according to the training environment and according to a plurality of generated training agents, each associated with one of the plurality of agent classes and one of the plurality of movement pattern classes; collecting simulated driving data from the simulated environment; and modifying at least one model parameter of the simulation generation model to minimize a difference between a simulation statistical fingerprint, computed using the simulated driving data, and a real statistical fingerprint, computed using the real datType: ApplicationFiled: October 15, 2019Publication date: October 7, 2021Applicant: Cognata Ltd.Inventors: Dan ATSMON, Eran ASA, Ehud SPIEGEL
-
Patent number: 11100371Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.Type: GrantFiled: October 7, 2019Date of Patent: August 24, 2021Assignee: Cognata Ltd.Inventors: Dan Atsmon, Eran Asa, Ehud Spiegel
-
Publication number: 20200210779Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.Type: ApplicationFiled: October 7, 2019Publication date: July 2, 2020Applicant: Cognata Ltd.Inventors: Dan ATSMON, Eran ASA, Ehud SPIEGEL
-
Patent number: 10460208Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: producing a plurality of synthetic training signals, each simulating one of a plurality of signals simultaneously captured from a common training scene by a plurality of sensors, and a plurality of training depth maps each qualifying one of the plurality of synthetic training signals according to the common training scene; training a machine learning model based on the plurality of synthetic training signals and the plurality of training depth maps; using the machine learning model to compute a plurality of computed depth maps based on a plurality of real signals, the plurality of real signals are captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of the plurality of sensors, each of the plurality of computed depth maps.Type: GrantFiled: January 2, 2019Date of Patent: October 29, 2019Assignee: Cognata Ltd.Inventors: Dan Atsmon, Eran Asa
-
Publication number: 20180349526Abstract: A computer implemented method of creating data for a host vehicle simulation, comprising: in each of a plurality of iterations of a host vehicle simulation using at least one processor for: obtaining from an environment simulation engine a semantic-data dataset representing a plurality of scene objects in a geographical area, each one of the plurality of scene objects comprises at least object location coordinates and a plurality of values of semantically described parameters; creating a 3D visual realistic scene emulating the geographical area according to the dataset; applying at least one noise pattern associated with at least one sensor of a vehicle simulated by the host vehicle simulation engine on the virtual 3D visual realistic scene to create sensory ranging data simulation of the geographical area; converting the sensory ranging data simulation to an enhanced dataset emulating the geographical area, the enhanced dataset comprises a plurality of enhanced scene objects.Type: ApplicationFiled: May 29, 2018Publication date: December 6, 2018Inventors: Dan Atsmon, Guy Tsafrir, Eran Asa