Embodiments are provided that include maintaining a map of a plurality of markers in an environment. The map includes a last detection time of each marker of the plurality of markers. The embodiments also include receiving a set of detected markers from a robotic device that is configured to localize in the environment using the plurality of markers. The embodiments further include updating, in the map, the last detection time of each marker which has a mapped position that corresponds to a detected position of a detected marker in the set of detected markers. The embodiments additionally include identifying, from the plurality of markers in the map, a marker having a last detection time older than a threshold amount of time. The embodiments still further include initiating an action related to the identified marker.

The present disclosure relates to a system for generating a digital map of an environment. The system comprises at least one sensor which is configured to record sensor data and a position of an object within the environment together with a time-stamp of recording the sensor data. Further, the system comprises a data processing circuitry configured to determine a time-dependent presence probability distribution of the object based on the sensor data. The presence probability distribution is indicative of a probability of the object being at its position before, after and/or at a time of the time-stamp. The data processing circuitry is further configured to register the presence probability distribution of the object in the digital map of an environment of the object.

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 method and an electronic device for determining a presence of an obstacle in a surrounding area of a self-driving car (SDC) are provided. The method comprises receiving sensor data representative of the surrounding area of the SDC in a form of 3D point cloud data; generating, by an MLA, based on the 3D point cloud data, a set of feature vectors representative of the surrounding area; generating, by the MLA, a grid representation of the surrounding area, each given cell of the grid representation including a predicted distance parameter indicative of a distance from the given cell to a closest cell with the obstacle; and using, by the electronic device, the distance parameter to determine presence of the obstacle in the surrounding area of the SDC.

A method for the simultaneous localization and mapping in 2D using a 3D scanner. An environment is scanned with the aid of the 3D scanner in order to generate a three-dimensional representation of the environment in the form of a 3D pixel cloud made up of a multitude of scanned pixels. A two-dimensional representation of the environment in the form of a 2D pixel cloud is subsequently generated from the 3D pixel cloud. The 2D pixel cloud is conveyed to a 2D SLAM algorithm for the generation of a map of the environment and for the simultaneous ascertainment of the current position of the 3D scanner within the map.

Disclosed are a map construction method, a robot, and a storage medium. A center of a lidar of a mapping robot is taken as a starting point, and a radar probe is arranged according to a preset distance; the radar probe is configured to determine a reference point cloud; the lidar of the mapping robot is controlled to scan the target environment to obtain scanning data; the target environment includes a wall and an obstacle; according to the scanning data, a virtual wall corresponding to the wall is determined; according to the scanning data, the reference point cloud determined by the radar probe is fitted to update the virtual wall to obtain an updated virtual wall; a target map including the updated virtual wall is generated.

Disclosed embodiments include computer-implemented methods, systems, and vehicles for detecting an intention to make a turn and automatically changing a view presented by the navigation system to increase a viewable portion of the turn. In an illustrative embodiment, a system includes a computing device that includes a processor and computer-readable media configured to store computer-executable instructions configured to cause the processor to: detect that a navigation system of a vehicle is operating without a predetermined destination; identify an intention of an operator to turn the vehicle; and, responsive to identifying the intention to turn the vehicle, automatically adjusting a view presented by a display of the navigation system to increase a viewable portion of the turn.

A system and method for the classification of geographic locations based on vehicle trip logs, including: grouping a plurality of trip records by vehicle, wherein the plurality of trip records include start times and locations and stop times and locations; sorting the plurality of trip records for a vehicle in one of descending or ascending order with respect to stop times; calculating a plurality of time differences between consecutive trips of the plurality of trip records; storing the plurality of time differences in a stop time array; for a first plurality of time differences, storing the associated stop locations in a first location array; for a second plurality of stop times, storing the associated stop locations in a second location array; and computing a time difference median for each of the first location array and the second location array and returning the time difference medians as results for each location.

An information processing device that can show an area in which reliable autonomous traveling is possible acquires history information of a position/orientation of a moving body estimated based on a captured image from a camera mounted on the moving body, acquires obstacle arrangement information indicating an arrangement of obstacles in a space where the moving body moves, acquires autonomous traveling possibility information indicating an area in which a setting for causing the moving body to autonomously travel is possible based on the history information, and generates a map image showing the arrangement of obstacles and the area in which autonomous traveling is possible based on the obstacle arrangement information and the autonomous traveling possibility information.

Systems and methods for generating mapping data for an autonomous vehicle (e.g., robotic devices). The methods include obtaining three-dimensional environmental data of an environment from a distance sensor. The three-dimensional environmental data includes information relating to one or more objects in the environment. The method further includes identifying at least one planar layer of two-dimensional data from the three-dimensional environmental data to be included in mapping data based on one or more characteristics of an autonomous vehicle, generating mapping data comprising the at least one planar layer of two-dimensional data from the three-dimensional environmental data, and transmitting the mapping data to the autonomous vehicle for use during operation within the environment.