Abstract: A computer that includes a processor and a memory, the memory including instructions executable by the processor to input an image to a first neural network to generate a first detected object and input the image to a second neural network to generate a reconstructed image which is input to a third neural network to generate a second detected object. The image can be divided into portions and the portions input to respective fourth neural networks to generate portions of a third detected object. The first detected object, the second detected object, the portions of the third detected object, and context data can be input to a partially observable Markov decision process to generate a high confidence detected object.

Abstract: A vehicle power supply device is provided. The vehicle power supply device includes: a fixed base; a scissor-fork lifting mechanism, where the scissor-fork lifting mechanism is mounted on the fixed base; a power supply head, where the power supply head is mounted on the scissor-fork lifting mechanism and is driven by the scissor-fork lifting mechanism to ascend or descend; and a drive device, where the drive device includes a drive unit and a transmission unit configured to convert rotational movement into linear movement. The drive unit and the transmission unit are stacked along a lifting direction of the scissor-fork lifting mechanism. The drive unit is connected with the scissor-fork lifting mechanism by the transmission unit to drive the scissor-fork lifting mechanism to ascend or descend.

Abstract: A system receives identification of data to be gathered, via a request configured based on a configuration file associated with a machine learning model stored by a vehicle. The system receives identification of how the data is to be labeled, defined by the configuration file and create one or more topics for publication of the data, onboard the vehicle, the publication including both the gathered data and any meta-data usable to label the data in accordance with the definitions in the configuration file. Also, the system subscribes to the topics to receive the published data and the metadata and appends labels to the data, using the metadata, to label the data in accordance with the definitions for labeling in the configuration file. The system saves the labeled data in vehicle memory as data associated with the model.

Abstract: A system subscribes to one or more inference topics to which inferences are published on behalf of trainable software models executing in a vehicle computing environment. The system receives inferences from the topics as the inferences are published to the topics and associates the inferences with one or more trainable software models to be monitored. Also, the system identifies instances of unexpected output based on comparison of received inferences, associated with a given model to be monitored, to expected inference values identified in a configuration file, stored in a vehicle memory and associated with the given model, and, responsive to identifying the unexpected output, devises a modification strategy for the model based on characteristics of the unexpected output.

Abstract: A system receives identification of a machine learning model, stored by a vehicle, that is ready for training. The system determines, based on a configuration file associated with the model, whether batch-based or live training is to be used to train the model and collects data for training, defined by a configuration file associated with the model. The system calls a learning as a service vehicle process to load a kernel and configures the kernel based on configuration data defined in the configuration file. The system receives notification from the learning as a service process that the training is complete. Additionally, the system validates a model, responsive to the notification including indication that training was successful, using a vehicle model validation process to test the model with live data before deployment by background execution of the model and saves a copy of the model for deployment responsive to successful validation.

Abstract: A vehicle power supply device is provided. The vehicle power supply device includes: a fixed base; a scissor-fork lifting mechanism, where the scissor-fork lifting mechanism is mounted on the fixed base; a power supply head, where the power supply head is mounted on the scissor-fork lifting mechanism and is driven by the scissor-fork lifting mechanism to ascend or descend; and a drive device, where the drive device includes a drive unit and a transmission unit configured to convert rotational movement into linear movement. The drive unit and the transmission unit are stacked along a lifting direction of the scissor-fork lifting mechanism. The drive unit is connected with the scissor-fork lifting mechanism by the transmission unit to drive the scissor-fork lifting mechanism to ascend or descend.

Abstract: A vehicle power supply device is provided. The vehicle power supply device includes: a fixed base; a scissor-fork lifting mechanism, where the scissor-fork lifting mechanism is configured to be driven by a drive device to ascend or descend; and the scissor-fork lifting mechanism includes at least one scissor-fork swing rod set, the scissor-fork swing rod set includes at least one pair of swing rods, each pair of swing rods includes two swing rods that are cross-arranged and are hinged with each other, and two swing rods in a pair of swing rods that is closest to the fixed base are separately mounted on the fixed base; and a power supply head, where the power supply head is mounted on two swing rods in a pair of swing rods that is farthest from the fixed base, and the power supply head is driven by the scissor-fork lifting mechanism to ascend or descend.

Abstract: A system for reducing the likelihood of a battery short during a collision of a vehicle includes a metallic structure coupled to a portion of the vehicle. The system further includes a battery located proximate to the metallic structure and having a positive terminal. The system further includes an insulator coupled to the metallic structure such that it is located between the metallic structure and the positive terminal of the battery and configured to resist contact between the metallic structure and the positive terminal of the battery in response to the collision of the vehicle.

Abstract: A system for reducing the likelihood of a battery short during a collision of a vehicle includes a metallic structure coupled to a portion of the vehicle. The system further includes a battery located proximate to the metallic structure and having a positive terminal. The system further includes an insulator coupled to the metallic structure such that it is located between the metallic structure and the positive terminal of the battery and configured to resist contact between the metallic structure and the positive terminal of the battery in response to the collision of the vehicle.

Abstract: A navigation system includes: an image capture unit, configured to capture a gesture; a control unit, coupled to the image capture unit, configured to distinguish between a command motion and a natural motion based on the gesture, an auditory cue, and a contextual information; and generate a command combination for instructing the navigation system based on the command motion and the auditory cue.

Abstract: A navigation system includes: an image capture unit, configured to capture a gesture; a control unit, coupled to the image capture unit, configured to distinguish between a command motion and a natural motion based on the gesture, an auditory cue, and a contextual information; and generate a command combination for instructing the navigation system based on the command motion and the auditory cue.