Among other things, techniques for detecting objects in the environment surrounding a vehicle are described. A computer system is configured to receive a set of measurements from a sensor of a vehicle. The set of measurements includes a plurality of data points that represent a plurality of objects in a 3D space surrounding the vehicle. The system divides the 3D space into a plurality of pillars. The system then assigns each data point of the plurality of data points to a pillar in the plurality of pillars. The system generates a pseudo-image based on the plurality of pillars. The pseudo-image includes, for each pillar of the plurality of pillars, a corresponding feature representation of data points assigned to the pillar. The system detects the plurality of objects based on an analysis of the pseudo-image. The system then operates the vehicle based upon the detecting of the objects.

Provided are an electronic control device and a vehicle control system capable of reducing a calculation amount and improving reliability of a travel route of a vehicle as compared with a conventional course setting device. An electronic control device 200 is mounted on a vehicle 100. The electronic control device 200 includes a map processing device 210 connected to an external sensor 110 that recognizes an obstacle around the vehicle 100 and a position sensor 120 that acquires position information of the vehicle 100 in a manner capable of information communication. The map processing device 210 includes a storage device 212 that stores map information including travel route information of the vehicle 100. The map processing device 210 records a travel route along which the vehicle 100 avoids an obstacle in the storage device 212, classifies the obstacle into a permanent obstacle and a transient obstacle, and updates the travel route information with an avoiding route based on the travel route along which the vehicle 100 has avoided the permanent obstacle.

The present disclosure discloses a median line method in maritime delimitation based on an earth ellipsoid. The method is implemented by calculating a coordinate point of a median line of a maritime space, including: determining two delimitation base points A and B on a coastline of a certain country and a delimitation base point C on a coastline of the other country; calculating to obtain an equidistant point O with the same geodetic distance from the two points A and B; solving the geodetic distance from the point O to the point C according to the geodetic coordinates of the equidistant point O; determining whether the difference between respective geodetic distances of OC and OA is less than a first target error; if the difference is less than the first target error, then taking O as a point on a solved median line; and otherwise, adjusting the geodetic distance, and recalculating the coordinates of the point O.

The present disclosure provides a method for parking a vehicle, an electronic device and a medium. The method comprises: acquiring parking environment data of a parking environment related to a vehicle and historical parking data in the parking environment; selecting, according to the parking environment data and the historical parking data, a constraint set for parking the vehicle from a plurality of constraint sets, the plurality of constraint sets corresponding to a corresponding parking risk level; and controlling the vehicle to park according to the selected constraint set.

The present disclosure proposes a method and an apparatus for recognizing a stuck status as well as a computer storage medium, with the method comprising: building an environmental map within a preset extent by taking the current position of the mobile robot as center; real-time monitoring the march information of the mobile robot and predicting whether the mobile robot is stuck or not; acquiring data from multiple sensors of the mobile robot, if the mobile robot is stuck; and recognizing the current stuck status of the mobile robot based on the data from multiple sensors.

The disclosure provides a plant blooming period broadcast method and system, and a computer-readable storage medium. The method comprises: receiving an image, and identifying a plant in the image to obtain the species of the plant; using a plant variety identification model corresponding to the species of the plant to identify the specific variety and blooming state of the plant; obtaining the photographing time and photographing position of the image, and determining the blooming period of the plant according to the photographing time and the blooming state; and marking the photographing position on a blooming period broadcast map as a viewing place of the plant, and correspondingly displaying the specific variety and blooming period of the plant.

Systems including one or more sensors, coupled to a vehicle, may detect sensor information and provide the sensor information to another computing device for processing. A system includes one or more sensors, coupled to a vehicle and configured to detect sensor information, and a computing device configured to communicate with one or more mobile sensors to receive the mobile sensor information, communicate with the one or more sensors to receive the sensor information, and analyze the sensor information and the mobile sensor information to identify one or more risk factors.

A system for the remote care of an item of vegetation used as a potential source of food for an animal, to include at least one of a proximity tag, RFID tag, transponder device, a predetermined machine-readable pattern, and geo-location device associated with the item of vegetation, and an aerial drone. The aerial drone includes a microprocessor, a sensor coupled to the microprocessor and configured to detect the at least one of the proximity tag, RFID tag, transponder device, predetermined machine-readable pattern, and the geo-location device, and a carrier configured to carry a substance comprising at least one of a solid, gas, and liquid. The aerial drone is configured to act in response to instructions issued by the microprocessor.

The present technology provides systems, methods, and devices that can update aspects of a map as an autonomous vehicle navigates a route, and therefore avoids the need for dispatching a special purpose mapping vehicle for these updates. As the autonomous vehicle navigates the route, data captured by at least one sensor of an autonomous vehicle can indicate an inconsistency between pre-mapped from a high-resolution sensor system describing a location on a map, and current data describing a new feature of the location. The current data can be clustered together based on a threshold spatial closeness, where the clustering describes the new feature, and semantic labels of the pre-mapped data from the high-resolution sensor system can be updated based on the new feature described by the clustered current data.

A vehicle data collection system includes a vehicle-mounted sensor; a non-transitory computer readable medium configured to store instructions; and a processor connected to the non-transitory computer readable medium. The processor is configured to execute the instructions for generating an invariant feature map, using a first neural network; and comparing the invariant feature map to template data to determine a similarity between the invariant feature map and the template data, wherein the template data is received from a server. The processor is further configured to execute the instructions for determining whether the determined similarity is exceeds a predetermined threshold; and instructing a transmitter to send the sensor data to the server in response to a determination that the determined similarity exceeds the predetermined threshold.