-
公开(公告)号：US11488395B2
公开(公告)日：2022-11-01
申请号：US16589532
申请日：2019-10-01
Applicant: Toyota Research Institute, Inc.
Inventor： Shunsho Kaku , Ryan W. Wolcott
Abstract: Systems and methods for vehicular navigation are disclosed herein. One embodiment receives, from one or more sensors, sensor data pertaining to a roadway section that is proximate to a vehicle; generates segmented sensor data to identify, in the roadway section, one or more boundary lines of one or more lanes; determines, from the sensor data, a direction of travel associated with at least one of the one or more lanes; applies a graphical model to the segmented sensor data to generate an output that includes a set of discrete points corresponding to the one or more boundary lines; generates an objective map of the roadway section from the set of discrete points; and uses the objective map to assist the vehicle in navigating the roadway section.
-
公开(公告)号：US20220269891A1
公开(公告)日：2022-08-25
申请号：US17184773
申请日：2021-02-25
Applicant: Toyota Research Institute, Inc.
Inventor： Shunsho Kaku , Jeffrey M. Walls , Ryan W. Wolcott
Abstract: A neural network can be configured to produce an electronic road map. The electronic road map can have information to distinguish lanes of a road. A feature in an image can be detected. The image can have been produced at a current time. The image can be of the road. The feature in the image can be determined to correspond to a feature, of a plurality of features, in a feature map. The feature map can have been produced at a prior time from one or more images. A labeled training map can be produced from the feature in the image and the plurality of features in the feature map. The labeled training map can have the information to distinguish the lanes of the road. The neural network can be trained to produce, in response to a receipt of the image and the feature map, the labeled training map.
-
3.发明授权公开(公告)号：US11067693B2
公开(公告)日：2021-07-20
申请号：US16033289
申请日：2018-07-12
Applicant: Toyota Research Institute, Inc.
Inventor： Jeffrey M. Walls , Ryan W. Wolcott
Abstract: System, methods, and other embodiments described herein relate to calibrating a light detection and ranging (LiDAR) sensor with a camera sensor. In one embodiment, a method includes controlling i) the LiDAR sensor to acquire point cloud data, and ii) the camera sensor to acquire an image. The point cloud data and the image at least partially overlap in relation to a field of view of a surrounding environment. The method includes projecting the point cloud data into the image to form a combined image. The method includes adjusting sensor parameters of the LiDAR sensor and the camera sensor according to the combined image to calibrate the LiDAR sensor and the camera sensor together.
-
公开(公告)号：US10989562B2
公开(公告)日：2021-04-27
申请号：US16033275
申请日：2018-07-12
Applicant: Toyota Research Institute, Inc.
Inventor： Paul J. Ozog , Ryan W. Wolcott , Schuyler H. Cohen
Abstract: System, methods, and other embodiments described herein relate to improving calibration of an onboard sensor of a vehicle. In one embodiment, a method includes, in response to acquiring sensor data from a surrounding environment of the vehicle using the onboard sensor, analyzing the sensor data to determine calibration parameters for the onboard sensor. The method includes identifying a suitability parameter that characterizes how well the surrounding environment provides for determining the calibration parameters. The method includes generating annotations within a map that specify at least the suitability parameter for a location associated with the sensor data. In further aspects, the method includes identifying, from the map, a calibration route for the vehicle that is a deviation from a current route in response to determining that the calibration state of the onboard sensor does not satisfy the calibration threshold.
-
公开(公告)号：US20200018612A1
公开(公告)日：2020-01-16
申请号：US16035992
申请日：2018-07-16
Applicant: Toyota Research Institute, Inc.
Inventor： Ryan W. Wolcott
Abstract: The systems and methods described herein disclose detecting events in a vehicular environment using vehicle behavior. As described here, vehicles, either manual or autonomous, that detect an event in the environment will operate to respond to the event. As such, those movements can be used to determine if an event has occurred, even if the event cannot be determined directly. The systems and methods can include collecting detection data about a vehicle behaviors in a vehicular environment. Event behaviors can then be selected from the vehicle behaviors. A predicted event can be formulated based on the event behaviors. The predicted event and an event location can be associated in the vehicular environment. A guidance input can then be formulated for a recipient vehicle. Finally, a recipient vehicle can be navigated using the guidance input.
-
Patent Agency Ranking
公开(公告)号：US11741724B2
公开(公告)日：2023-08-29
申请号：US17184773
申请日：2021-02-25
Applicant: Toyota Research Institute, Inc.
Inventor： Shunsho Kaku , Jeffrey M. Walls , Ryan W. Wolcott
CPC classification number: G06V20/588 , G06F18/21 , G06N3/047 , G06N3/08 , G06V20/52 , G06V30/194
Abstract: A neural network can be configured to produce an electronic road map. The electronic road map can have information to distinguish lanes of a road. A feature in an image can be detected. The image can have been produced at a current time. The image can be of the road. The feature in the image can be determined to correspond to a feature, of a plurality of features, in a feature map. The feature map can have been produced at a prior time from one or more images. A labeled training map can be produced from the feature in the image and the plurality of features in the feature map. The labeled training map can have the information to distinguish the lanes of the road. The neural network can be trained to produce, in response to a receipt of the image and the feature map, the labeled training map.
-
公开(公告)号：US20220219725A1
公开(公告)日：2022-07-14
申请号：US17145767
申请日：2021-01-11
Applicant: Toyota Research Institute, Inc.
Inventor： Wolfram Burgard , Ryan W. Wolcott
Abstract: An autonomous vehicle can be navigated through an intersection. Topological information about the intersection can be obtained. The topological information can include, for example, a count of a number of lanes on roads associated with the intersection, information about an entrance point to the intersection, or information about an exit point from the intersection. Based on the topological information, context information about a candidate trajectory through the intersection can be obtained. For example, the context information can be based on a current time or information about a position of an object with respect to the topological information. Based on the context information, an existence of an advantage to change an actual trajectory of the autonomous vehicle can be determined. In response to a determination of the existence of the advantage, a change to the actual trajectory of the autonomous vehicle can be caused to occur.
-
公开(公告)号：US20220114375A1
公开(公告)日：2022-04-14
申请号：US17066351
申请日：2020-10-08
Applicant: TOYOTA RESEARCH INSTITUTE, INC.
Inventor： Kun-Hsin Chen , Peiyan Gong , Sunsho Kaku , Sudeep Pillai , Hai Jin , Sarah Yoo , David L. Garber , Ryan W. Wolcott
Abstract: Systems and methods are provided for developing/updating training datasets for traffic light detection/perception models. V2I-based information may indicate a particular traffic light state/state of transition. This information can be compared to a traffic light perception prediction. When the prediction is inconsistent with the V2I-based information, data regarding the condition(s)/traffic light(s)/etc. can be saved and uploaded to a training database to update/refine the training dataset(s) maintained therein. In this way, an existing traffic light perception model can be updated/improved and/or a better traffic light perception model can be developed.
-
公开(公告)号：US10753750B2
公开(公告)日：2020-08-25
申请号：US16033281
申请日：2018-07-12
Applicant: Toyota Research Institute, Inc.
Inventor： Ryan W. Wolcott , Jeffrey M. Walls
Abstract: System, methods, and other embodiments described herein relate to improving mapping of a surrounding environment by a mapping vehicle. In one embodiment, a method includes identifying dynamic objects within the surrounding environment that are proximate to the mapping vehicle from sensor data of at least one sensor of the mapping vehicle. The dynamic objects are trackable objects that are moving within the surrounding environment. The method includes generating paths of the dynamic objects through the surrounding environment relative to the mapping vehicle according to separate observations of the dynamic objects embodied within the sensor data. The method includes producing a map of the surrounding environment from the paths.
-
公开(公告)号：US20180307915A1
公开(公告)日：2018-10-25
申请号：US15495735
申请日：2017-04-24
Applicant: Toyota Research Institute, Inc.
Inventor： Edwin B. Olson , Michael R. James , Ryan M. Eustice , Ryan W. Wolcott
CPC classification number: G06K9/00791 , G05D1/0248 , G05D1/0251 , G06K9/6215 , G06K9/6267
Abstract: System, methods, and other embodiments described herein relate to identifying changes between models of a locality. In one embodiment, a method includes, in response to determining that a location model is available for a present environment of a vehicle, generating a current model of the present environment using at least one sensor of the vehicle. The method also includes isolating dynamic objects in the current model as a function of the location model. The method includes providing the dynamic objects to be identified and labeled.
-
-
-
-
-
-
-
-
-
Search Results
30
records
(took 0.018 seconds)
