Abstract: A method and electronic device for detecting an object are disclosed. The method includes generating a cluster of points representative of the surroundings of the SDC, generating by a first Neural Network (NN) a first feature vector based on the cluster indicative of a local context of the given object in the surroundings of the SDC, generating by a second NN second feature vectors for respective points from the cluster based on a portion of the point cloud, where a given second feature vector is indicative of the local and global context of the given object, generating by the first NN a third feature vector for the given object based on the second feature vectors representative of the given object, and generating by a third NN a bounding box around the given object using the third feature vector.

Abstract: A method and system for providing scan data for decision making in a self-driving vehicle are provided. The self-driving vehicle includes a scanning sensor that scans a space around the self-driving vehicle in consecutive scanning cycles. The method includes receiving a request for scan information associated with a requested segment of space. The method determines whether to wait for a next scan of the requested segment and use scan data from the next scan, or to extract and use scan data from a previous scan of the requested segment. The method also includes processing the scan data to generate the scan information for the requested segment, providing the scan information for the requested segment in response to the request, and operating the self-driving vehicle in accordance with a decision made about a maneuver to be performed by the self-driving vehicle based, at least in part, on the scan information.

Abstract: A method and electronic device for detecting an object are disclosed. The method includes generating a cluster of points representative of the surroundings of the SDC, generating by a first Neural Network (NN) a first feature vector based on the cluster indicative of a local context of the given object in the surroundings of the SDC, generating by a second NN second feature vectors for respective points from the cluster based on a portion of the point cloud, where a given second feature vector is indicative of the local and global context of the given object, generating by the first NN a third feature vector for the given object based on the second feature vectors representative of the given object, and generating by a third NN a bounding box around the given object using the third feature vector.

Abstract: A method for determining a set of dynamic objects in sensor data representative of a surrounding area of a vehicle having sensors, the method being executed by a server, the server executing a machine learning algorithm (MLA). Sensor data is received, and the MLA generates, based on the sensor data, a set of feature vectors. Vehicle data indicative of a localization of the vehicle is received. The MLA generates, based on the set of feature vectors and the vehicle data, a tensor, the tensor including a grid representation of the surrounding area. The MLA generates an mobility mask indicative of grid cells occupied by at least one moving potential object in the grid, and a velocity mask indicative of a velocity associated with the at least one potential object in the grid. The MLA determines, based on the mobility mask and the velocity mask, the set of dynamic objects.

Abstract: A method and system for providing scan data for decision making in a self-driving vehicle are provided. The self-driving vehicle includes a scanning sensor that scans a space around the self-driving vehicle in consecutive scanning cycles. The method includes receiving a request for scan information associated with a requested segment of space. The method determines whether to wait for a next scan of the requested segment and use scan data from the next scan, or to extract and use scan data from a previous scan of the requested segment. The method also includes processing the scan data to generate the scan information for the requested segment, providing the scan information for the requested segment in response to the request, and operating the self-driving vehicle in accordance with a decision made about a maneuver to be performed by the self-driving vehicle based, at least in part, on the scan information.

Abstract: A method for determining a set of dynamic objects in sensor data representative of a surrounding area of a vehicle having sensors, the method being executed by a server, the server executing a machine learning algorithm (MLA). Sensor data is received, and the MLA generates, based on the sensor data, a set of feature vectors. Vehicle data indicative of a localization of the vehicle is received. The MLA generates, based on the set of feature vectors and the vehicle data, a tensor, the tensor including a grid representation of the surrounding area. The MLA generates an mobility mask indicative of grid cells occupied by at least one moving potential object in the grid, and a velocity mask indicative of a velocity associated with the at least one potential object in the grid. The MLA determines, based on the mobility mask and the velocity mask, the set of dynamic objects.