Ford Global Technolgoies, LLC

Argo Ai Gmbh

Basel Alghanem

G Peter K Carr

Arsenii Saranin

Benjamin D Ballard

Jason Ziglar

Russell Schloss

Mark Ollis

Kevin Lee Wyffels

George Peter Kenneth Carr

Shadi Jammoul

Nicolas Vandapel

Christian Höeppner

Yujun Wang

Limin Wu

Systems and methods are described for measuring velocity of an object detected by a light detection and ranging (lidar) system. According to some aspects a method may include receiving a lidar dataset generated by the lidar system, transforming the lidar dataset into a first layer dataset and a second layer dataset, and converting the first layer dataset into a first image and the second layer dataset into a second image. The method may also include performing a feature detection operation that identifies at least one feature in the first image and the same feature in the second image, locating a first location of the feature in the first image and a second location of the feature in the second image, and generating a velocity estimate of the feature based on a difference between the first location and the second location and a difference between the different time intervals.

Systems and method for lidar grid velocity estimation

Systems and methods for object detection. Object detection may be used to control autonomous vehicle(s). For example, the methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of the autonomous vehicle; and using, by the computing device. The LiDAR dataset and image(s) are used to detect an object that is in proximity to the autonomous vehicle. The object is detected by: computing a distribution of object detections that each point of the LiDAR dataset is likely to be in; creating a plurality of segments of LiDAR data points using the distribution of object detections; and detecting the object in a point cloud defined by the LiDAR dataset based on the plurality of segments of LiDAR data points. The object detection may be used to facilitate at least one autonomous driving operation.

Systems and methods for camera-LiDAR fused object detection with local variation segmentation

Systems and methods for object detection. Object detection may be used to control autonomous vehicle(s). For example, the methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of the autonomous vehicle; and using, by the computing device, the LiDAR dataset and image(s) to detect an object that is in proximity to the autonomous vehicle. The object being is detected by: computing a distribution of object detections that each point of the LiDAR dataset is likely to be in; creating a plurality of segments of LiDAR data points using the distribution of object detections; merging the plurality of segments of LiDAR data points to generate merged segments; and detecting the object in a point cloud defined by the LiDAR dataset based on the merged segments. The object detection may be used by the computing device to facilitate at least one autonomous driving operation.

Systems and methods for camera-LiDAR fused object detection with segment merging

Systems/methods for object detection. The methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of the autonomous vehicle; and using, by a computing device, the LiDAR dataset and at least one image to detect an object that is in proximity to the autonomous vehicle. The object is detected by: generating a pruned LiDAR dataset by reducing a total number of points contained in the LiDAR dataset; and detecting the object in a point cloud defined by the pruned LiDAR dataset. The object detection may be used by the computing device to facilitate at least one autonomous driving operation.

Systems and methods for camera-LiDAR fused object detection with point pruning

Systems and methods for complementary control of an autonomous vehicle (AV) are disclosed. The methods include receiving information comprising an active trajectory of an AV that the AV intends to following for a planning horizon. The methods also include using the active trajectory to identify one or more regions in an environment of the AV such as a fallback monitoring region (FMR) and an active monitoring region (AMR), and generating one or more instructions for causing the AV to execute a collision mitigation action in response to an object being detected within the AMR. The methods further include transmitting the one or more instructions to an AV platform (AVP) for execution.

Complementary control system for an autonomous vehicle

Systems and methods for object detection. The object detection may be used to control an autonomous vehicle. For example, the methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of the autonomous vehicle; and using, by the computing device, the LiDAR dataset and at least one image to detect an object that is in proximity to the autonomous vehicle. The object is detected by: matching points of the LiDAR dataset to pixels in the at least one image; and detecting the object in a point cloud defined by the LiDAR dataset based on the matching. The object detection may be used to facilitate at least one autonomous driving operation (e.g., autonomous driving operation comprises an object tracking operation, an object trajectory prediction operation, a vehicle trajectory determination operation, and/or a collision avoidance operation).

Systems and methods for camera-LiDAR fused object detection with LiDAR-to-image detection matching

Systems and methods for object detection. Object detection may be used to control autonomous vehicle(s). For example, the methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of autonomous vehicle; and using, by the computing device, the LiDAR dataset and image(s) to detect an object that is in proximity to the autonomous vehicle. The object is detected by performing the following operations: computing a distribution of object detections that each point of the LiDAR dataset is likely to be in; creating a plurality of segments of LiDAR data points using the distribution of object detections; merging the plurality of segments of LiDAR data points to generate merged segments; and detecting the object in a point cloud defined by the LiDAR dataset based on the merged segments. The object detection may be used by the computing device to facilitate at least one autonomous driving operation.

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Pittsburgh, PA, United States of America

Basel Alghanem