Abstract: Disclosed herein are methods and systems for measuring and mapping traffic signals in global coordinates. A method includes obtaining an image of an environment for a vehicle location, detecting a traffic signal in the image, classifying the detected traffic signal, obtaining traffic signal specification information associated with the classified traffic signal, determining a control point associated with the classified traffic signal, determining a 3D position of the control point in camera space using the traffic signal specification information, camera calibration information, image pixel size, and focal length of camera used in capturing the image, transforming the 3D position of the control point in the camera space to a 3D position of the control point in global coordinates, saving the 3D position of the control point in global coordinates in a map, and controlling operation of a vehicle with 3D positions of control points in global coordinates saved in the map.

Abstract: Methods and systems may be used for obtaining a high-confidence point-cloud. The method includes obtaining three-dimensional sensor data. The three-dimensional sensor data may be raw data. The method includes projecting the raw three-dimensional sensor data to a two-dimensional image space. The method includes obtaining sparse depth data of the two-dimensional image. The method includes obtaining a predicted depth map. The predicted depth map may be based on the sparse depth data. The method includes obtaining a predicted error-map. The predicted error map may be based on the sparse depth data. The method includes outputting a high-confidence point-cloud. The high-confidence point-cloud may be based on the predicted depth map and the predicted error-map.

Abstract: Methods and systems may be used for obtaining a high-confidence point-cloud. The method includes obtaining three-dimensional sensor data. The three-dimensional sensor data may be raw data. The method includes projecting the raw three-dimensional sensor data to a two-dimensional image space. The method includes obtaining sparse depth data of the two-dimensional image. The method includes obtaining a predicted depth map. The predicted depth map may be based on the sparse depth data. The method includes obtaining a predicted error-map. The predicted error map may be based on the sparse depth data. The method includes outputting a high-confidence point-cloud. The high-confidence point-cloud may be based on the predicted depth map and the predicted error-map.

Abstract: A vehicle subsystem includes an on-vehicle camera that is disposed to monitor a field of view (FOV) that includes a travel surface for the vehicle. A controller captures, via the on-vehicle camera, an image file associated with the FOV and segments the image file into a first set of regions associated with the travel surface and a second set of regions associated with an above-horizon portion. Image features on each of the first set of regions and the second set of regions are extracted and classified. A surface condition for the travel surface for the vehicle is identified based upon the classified extracted image features from each of the first set of regions and the second set of regions. Operation of the vehicle is controlled based upon the identified surface condition.

Abstract: Methods and system for compensating for vehicle system errors. A virtual camera is added to vehicle sensor configurations and a coordinate transformation process which attempts to match multiple 3D points associated with a landmark to a detected landmark. The virtual camera is associated with the detected landmark. The 3D world coordinate points may be transformed to a real 3D camera coordinate system and then to a virtual 3D camera coordinate system. The 3D points in real and virtual camera coordinate frames are projected onto the corresponding 2D image pixel coordinates, respectively. Inclusion of the virtual camera in the coordinate transformation process presents a 3D to 2D point corresponding problem which may be resolved using camera pose estimation algorithms. An offset compensation transformation matrix may be determined which accounts for errors contributed by mis-calibrated vehicle sensors or systems and applied to all data prior to use by the vehicle control systems.

Abstract: Methods and system for compensating for vehicle system errors. A virtual camera is added to vehicle sensor configurations and a coordinate transformation process which attempts to match multiple 3D points associated with a landmark to a detected landmark. The virtual camera is associated with the detected landmark. The 3D world coordinate points may be transformed to a real 3D camera coordinate system and then to a virtual 3D camera coordinate system. The 3D points in real and virtual camera coordinate frames are projected onto the corresponding 2D image pixel coordinates, respectively. Inclusion of the virtual camera in the coordinate transformation process presents a 3D to 2D point corresponding problem which may be resolved using camera pose estimation algorithms. An offset compensation transformation matrix may be determined which accounts for errors contributed by mis-calibrated vehicle sensors or systems and applied to all data prior to use by the vehicle control systems.

Abstract: A vehicle subsystem includes an on-vehicle camera that is disposed to monitor a field of view (FOV) that includes a travel surface for the vehicle. A controller captures, via the on-vehicle camera, an image file associated with the FOV and segments the image file into a first set of regions associated with the travel surface and a second set of regions associated with an above-horizon portion. Image features on each of the first set of regions and the second set of regions are extracted and classified. A surface condition for the travel surface for the vehicle is identified based upon the classified extracted image features from each of the first set of regions and the second set of regions. Operation of the vehicle is controlled based upon the identified surface condition.

Abstract: A vehicle includes a plurality of on-vehicle cameras, and a controller executes a method to evaluate a travel surface by capturing images for fields of view of the respective cameras. Corresponding regions of interest for the images are identified, wherein each of the regions of interest is associated with the portion of the field of view of the respective camera that includes the travel surface. Portions of the images are extracted, wherein each extracted portion is associated with the region of interest in the portion of the field of view of the respective camera that includes the travel surface and wherein one extracted portion of the respective image includes the sky. The extracted portions of the images are compiled into a composite image datafile, and an image analysis of the composite image datafile is executed to determine a travel surface state. The travel surface state is communicated to another controller.

Abstract: A vehicle includes a plurality of on-vehicle cameras, and a controller executes a method to evaluate a travel surface by capturing images for fields of view of the respective cameras. Corresponding regions of interest for the images are identified, wherein each of the regions of interest is associated with the portion of the field of view of the respective camera that includes the travel surface. Portions of the images are extracted, wherein each extracted portion is associated with the region of interest in the portion of the field of view of the respective camera that includes the travel surface and wherein one extracted portion of the respective image includes the sky. The extracted portions of the images are compiled into a composite image datafile, and an image analysis of the composite image datafile is executed to determine a travel surface state. The travel surface state is communicated to another controller.

Abstract: A method of identifying a snow covered road includes creating a forward image of a road surface. The forward image is analyzed to detect a tire track in the forward image. When a tire track is detected in the forward image, a message indicating a snow covered road surface is signaled. When a tire track is not detected in the forward image, a rearward image, a left side image, and a right side image are created. The rearward image, the left side image, and the right side image are analyzed to detect a tire track in at least one of the rearward image, the right side image, and the left side image. A message indicating a snow covered road surface is signaled when a tire track is detected in one of the rearward image, the left side image, or the right side image.

Abstract: A robot hand with a connection part that undergoes stretching deformation according to object shape. The robot hand includes a variable connection device that provides a contact face that enables pressing and contacting a moving target and has a connection part in contact with the moving target enables stretching deformation; a connection length controller that interfaces with a drive part to stretch and deform the connection part so that the connection part undergoes conversion between a closed-loop state wherein it is continuous with the surface of the moving target or divided into a plurality of sections to be pressed and contacted, and an open-loop state wherein it detaches from the moving target; and a shape retention device that retains the shape of the variable connection device consistently in a closed-loop state wherein the variable connection device is pressed and contacted with the moving target at a set pressure.

Abstract: The present invention relates to a robot hand with a connection part that undergoes stretching deformation according to object shape and a method for controlling a robot hand; the key technical point pertains to a robot hand with a connection part that undergoes stretching deformation according to object shape, comprising: a variable connection device (100) that provides a contact face that enables pressing and contacting a moving target (10) and has a structure wherein a connection part (100a) in contact with said moving target (10) enables stretching deformation; a connection length controller (200) that interfaces with a drive part such as a motor (201) or pump to stretch and deform the connection part (100a) of said variable connection device so that the connection part (100a) of said variable connection device undergoes conversion between a closed-loop state wherein it is continuous with the surface of said moving target (10) or divided into a plurality of sections to be pressed and contacted, and an ope