A method for updating a high definition map according to one embodiment comprises: obtaining a two-dimensional image that captures a target area corresponding to at least a part of an area expressed by a three-dimensional high definition map, generating a three-dimensional local landmark map of the target area from a position of a landmark in the two-dimensional image, based on a position and an orientation of a photographing device which has captured the two-dimensional image and updating the high definition map with reference to the local landmark map corresponding to the target area of the three-dimensional high definition map.

A method of complementing a map of a scene with 3D reference points including four steps. In a first step, data is collected and recorded based on samples of at least one of an optical sensor, a GNSS, and an IMU. A second step includes initial pose generation by processing of the collected sensor data to provide a track of vehicle poses. A pose is based on a specific data set, on at least one data set re-coded before that dataset and on at least one data set recorded after that data set. A third step includes SLAM processing of the initial poses and collected optical sensor data to generate keyframes with feature points. In a fourth step 3D reference points are generated by fusion and optimization of the feature points by using future and past feature points together with a feature point at a point of processing. This second and fourth steps provides significantly better results than SLAM or VIO methods known from prior art, as the second and the fourth steps are based on recorded data. Wherein a normal SLAM or VIO algorithm only can access data of the past, in these steps, processing may also be done by looking at positions ahead, by using the recorded data.

A measurement vehicle (101) acquires measurement environment data indicating a measurement environment from a measurement system and transmits the acquired measurement environment data to a base station (104). The measurement vehicle (101) receives movement measurement instruction data indicating an instruction on the movement measurement from the base station (104). The measurement vehicle (101) controls the measurement system in accordance with the instruction indicated by the received movement measurement instruction data.

A system and method for environmental parameter mapping. A method includes adding at least one entry to a mapping data structure, wherein each entry includes a position of a robotic device and at least one corresponding environmental parameter for the respective position of the robotic device, wherein each environmental parameter of each entry indicates an attribute of an environment at the corresponding position and is based on at least one sensor signal captured at the corresponding position; and sending at least one command to the robotic device, wherein the at least one command is determined based on the mapping data structure and includes at least one command to navigate.

Using key performance indicator (KPI) data sensed by vehicles is provided. A data server is programmed to receive, over a wide-area network from a plurality of vehicles, connectivity data of modems of the plurality of vehicles to the wide-area network, the connectivity data indicating KPI data, which road segment was being traversed when the KPI data was captured, and a time period during which the KPI data was captured. The data server is further programmed to identify outlier data elements in the KPI data using outlier detection criteria; and compile the KPI data per road segment and time period excluding the outlier data elements.

Techniques for collecting, synchronizing, and displaying various types of data relating to a road segment enable, via one or more local or remote processors, servers, transceivers, and/or sensors, (i) enhanced and contextualized analysis of vehicle events by way of synchronizing different data types, relating to a monitored road segment, collected via various different types of data sources; (ii) enhanced and contextualized analysis of filed insurance claims pertaining to a vehicle incident at a road segment; (iii) advantageous machine learning techniques for predicting a level of risk assumed for a given vehicle event or a given road segment; (iv) techniques for accounting for region-specific driver profiles when controlling autonomous vehicles; and/or (v) improved techniques for providing a GUI to display collected data in a meaningful and contextualized manner.

An agricultural baler system includes: an agricultural baler including a bale chamber configured to form a bale from crop material, a crop conveyor configured to feed crop material into the bale chamber, a location sensor configured to output a location signal corresponding to a location of the agricultural baler, and a parameter sensor configured to output a parameter signal corresponding to a measured parameter; and a controller operably coupled to the travel sensor and the parameter sensor. The controller is configured to: determine an area based at least partially on a rake width of a rake and a defined length; determine a parameter distribution in a region of a field having the area based at least partially on the measured parameter and the location of the agricultural baler; and output a field map update signal to update a field map to indicate the determined parameter distribution.

A navigation system for a vehicle comprises onboard sensors including a vision sensor, and an onboard map database of terrain maps. An onboard processer, coupled to the sensors and map database, includes a position PDF filter, which performs a method comprising: receiving image data from the vision sensor corresponding to terrain images captured by the vision sensor of a given area; receiving map data from the map database corresponding to a terrain map of the area; generating a first PDF of image features in the image data; generating a second PDF of map features in the map data; generating a measurement vector PDF by a convolution of the first PDF and second PDF; estimating a position vector PDF using a non-linear filter that receives the measurement vector PDF; and generating statistics from the estimated position vector PDF that include real-time measurement errors of position and angular orientation of the vehicle.

Systems and methods for scheduling environment perception-based data offloading for numerous connected vehicles are disclosed. In one embodiment, a method for offloading data includes capturing an image of a view of interest from a vehicle, segmenting the image into a plurality of blocks, and determining a scheduling priority for each of one or more blocks among the plurality of blocks based on block values, wherein the block values relate to one or more objects of interest contained in each of the one or more blocks. The method further includes offloading, from the vehicle to a server, one or more blocks based on the scheduling priority of the one or more blocks.

An ADV may determine whether there is preexisting map data for an environment or geographical area/location where the ADV is located/travelling. If there is no preexisting data, the ADV may generate map data based on sensor data obtained from one or more sensors of the ADV. The ADV may determine a path for the ADV based on the generated map data. If there is preexisting map data, the ADV may determine a path for the ADV based on the preexisting map data.