Abstract: A method and electronic device for controlling operation of a Self Driving Car (SDC) are disclosed. The method includes, at a given timestamps during operation of the SDC when located at a current location: generating a candidate location of the SDC using a localization algorithm, generating a parameter using a Machine Learning Algorithm (MLA) indicative of whether the localization algorithm is likely to generate divergent candidate locations for the SDC in a candidate portion of the map representation under a variety of conditions, determining that the localization algorithm to be an unreliable localization source in the candidate portion of the map representation using the parameter, determining a multi-sourced location of the SDC using data acquired from a reduced set of localization sources, the reduced set of sources excludes the localization algorithm, and controlling operation of the SDC using the multi-sourced location as the current location of the SDC.

Abstract: Method and device for processing LIDAR sensor data are disclosed. The method includes: receiving a first dataset and a second dataset having pluralities of data points; matching at least some of the plurality of first points with at least some of the plurality of second points, thereby determining a plurality of pairs; for the given one of the plurality of pairs, determining a pair-specific filtering parameter by calculating neighbour beam distances between the given first data point and respective ones the set of neighboring points, a given neighbour beam distance being representative of a linear distance between the given first data point and a respective one of the set of neighbouring points; in response to the pair-specific parameter being positive, excluding the given one of the plurality of pairs from further processing; and processing the reduced plurality of pairs for merging the first dataset and the second dataset.

Abstract: Method and device for processing LIDAR sensor data are disclosed. The method includes (i) receiving from the LIDAR sensor a first dataset having a plurality of first data points representative of respective coordinates and associated with respective normal vectors, (ii) determining an uncertainty parameter for a given first data point based on a normal covariance of the normal vector of the given first data point where the normal covariance takes into account a measurement error of the LIDAR sensor when determining the respective coordinates of the given first data point, (iii) in response to the uncertainty parameter being above a pre-determined threshold, excluding the given first data point from the plurality of first data points, (iv) using the filtered plurality of first data points, instead of the plurality of first data points, for merging the first dataset of the LIDAR sensor with a second dataset of the LIDAR sensor.

Abstract: Methods and server for updating a map representation of a geographical region is disclosed. For a given timestamp along a past trajectory of the SDC when the SDC has been located at a given location in the geographical region, the method includes: generating, using a localization algorithm, a set of candidate locations using a set of point clouds and the map representation, determining, using a convergence metric, a parameter for evaluating quality of localization of the localization algorithm when the SDC is located in the candidate portion of the map representation, identifying, using the parameter, the candidate portion of the map representation as an outdated portion of the map representation, and updating the outdated portion of the map representation using point cloud data captured by the LIDAR system.

Abstract: Method and device for processing LIDAR sensor data are disclosed. The method includes: receiving a first dataset and a second dataset having pluralities of data points; matching at least some of the plurality of first points with at least some of the plurality of second points, thereby determining a plurality of pairs; for the given one of the plurality of pairs, determining a pair-specific filtering parameter by calculating neighbour beam distances between the given first data point and respective ones the set of neighboring points, a given neighbour beam distance being representative of a linear distance between the given first data point and a respective one of the set of neighbouring points; in response to the pair-specific parameter being positive, excluding the given one of the plurality of pairs from further processing; and processing the reduced plurality of pairs for merging the first dataset and the second dataset.

Abstract: Method and device for processing LIDAR sensor data are disclosed. The method includes (i) receiving from the LIDAR sensor a first dataset having a plurality of first data points representative of respective coordinates and associated with respective normal vectors, (ii) determining an uncertainty parameter for a given first data point based on a normal covariance of the normal vector of the given first data point where the normal covariance takes into account a measurement error of the LIDAR sensor when determining the respective coordinates of the given first data point, (iii) in response to the uncertainty parameter being above a pre-determined threshold, excluding the given first data point from the plurality of first data points, (iv) using the filtered plurality of first data points, instead of the plurality of first data points, for merging the first dataset of the LIDAR sensor with a second dataset of the LIDAR sensor.