Abstract: A surveillance sensor system for a surveillance network configured to monitor an environment surrounding a device, and including a processing unit, a tridimensional sensor and a camera. The surveillance sensor system is providing to the surveillance network, a global tridimensional map, a plurality of features including associations of the features to the corresponding tridimensional data points in the global tridimensional map, and including properties determined for each feature. The surveillance sensor system is not providing the images from the camera to the surveillance network.

Abstract: A method for generating a colored tridimensional map of an environment surrounding a device, including the steps of receiving a first stream including a plurality of N point cloud frames from a tridimensional sensor, receiving a second stream including a plurality of M images from a camera, generating a global tridimensional map by merging the plurality of N point cloud frames in a reference coordinate system, and determining the colored tridimensional map by assigning a calculated color to each tridimensional data point of global tridimensional map, the calculated color being determined from color values of pixels of the plurality of M images.

Abstract: Provided is a method, system, and computer program product for avoiding ground blindness in a vehicle.

Abstract: A mobile entity including an imaging unit configured to generate at least a plurality of successive point cloud frames, and construct therefrom, via a simultaneous localization and mapping process, a floating map of a scene travelled by the mobile entity and a floating trajectory of the mobile entity, a geolocation system receiver, configured to deliver a plurality of successive geolocations, a computing unit configured to determine, via a best match process between the floating trajectory and the plurality of successive geolocations, an anchored trajectory, wherein the computing unit is configured to correct at least the latest geolocation into a corrected latest geolocation obtained from a projection of the latest geolocation on the anchored trajectory.

Abstract: We disclose adaptive active safety systems which utilize a sensing system to detect road conditions and actuate an active safety routine based thereon. One disclosed method includes transmitting, with a multispectral LIDAR system on a vehicle, a multispectral light beam directed at an anticipated region of travel of the vehicle within a road, and analyzing a response, of a photodetector, to a return of the multispectral light beam. The method also includes determining, based on the analyzing of the response, a hazardous surface condition in the anticipated region of travel of the vehicle, and actuating, based on the determination of the hazardous surface condition, an active safety routine. The method can be executed by an ADAS in which the determinations of the hazardous surface conditions on the road in the anticipated region of travel are executed in real time to thereby produce a road aware ADAS.

Abstract: A system including a radar configured to generate at least a first frame including a first point cloud and first relative speeds, an imager such as a Lidar configured to generate at least a second frame formed as an image and including a second point cloud and second relative speeds, at least a clock configured to generate first and second timestamps associated to the first frame and second frame respectively, a memory configured to store a map, a computing unit configured to update the map with a registration of the first point cloud data of the first frame using the first timestamp and the first relative speeds, and further configured to update the map with a registration of the second point cloud data of the second frame using the second timestamp and the relative speeds associated with the second frame. Map building method carried out in such a system.

Abstract: A method carried out in a system including at least a first imaging unit mounted on a first entity or first vehicle, at least a second imaging unit mounted on a second entity, the method including: —building, from the first imaging unit, a first map, formed as a floating map, through a simultaneous localization and mapping process; —building, from the second imaging unit, a second map; —establishing a data channel between first and second entities; —determining if there is at least an overlapping portion between first and second maps; —receiving, at the first entity, part or all the elements of the second map, from the second entity; —identifying matching candidate solutions to register the second map into the first map; and —registering and appending the second map to the first map of first vehicle.

Abstract: Disclosed is a method and a system for retrieving a location of a base point of a wheeled vehicle in a local coordinate system of a tridimensional sensor mounted on the vehicle. The method includes acquiring point cloud frames while the wheeled vehicle is moving along a straight path and a curved path and a point cloud representative of a portion of the vehicle, computing a main direction vector, a main direction line and a location of an instantaneous centre of rotation of the wheeled vehicle in the local coordinate system, and retrieving the location of the base point.

Abstract: A method for detecting intrusions in a monitored volume in which: N tridimensional sensors acquire local point clouds in respective local coordinate systems, a central processing unit receives the acquired local point clouds and, for each sensor, computes updated tridimensional position and orientation of the sensor in a global coordinate system of the monitored volume by aligning a local point cloud acquired by said tridimensional sensor with a global tridimensional map of the monitored volume, and generates an aligned local point cloud on the basis of the updated tridimensional position and orientation of the sensor, the central processing unit monitors an intrusion in the monitored volume by comparing a free space of the aligned local point cloud with a free space of the global tridimensional map.

Abstract: A method and a system for dynamically generating and updating a global tridimensional map of an environment surrounding one or several moving vehicles on which N tridimensional sensors are mounted and communicates with a central processing unit. Each sensor generates a continuous stream of point cloud frames, in parallel and asynchronously with the other sensors, the point cloud frames are representative of object surfaces located in a local volume of the environment surrounding each sensor. The central processing unit continuously receives the continuous streams from the sensors, store them in a memory and, for each newly received point cloud frame of each stream, generates or updates a global cumulated tridimensional map of the environment of the at least one vehicle by determining an aligned point cloud frame in a global coordinate system of the environment, and updating the global cumulated tridimensional map by merging the aligned point cloud frame.

Abstract: The invention belongs to motion detection and three-dimensional image analysis technology fields. It can be applied to movement detection or intrusion detection in the surveillance of monitored volumes or monitored spaces. It can also be applied to obstacle detection or obstacle avoidance for self-driving, semi-autonomous vehicles, safety systems and ADAS. A three-dimensional imaging system stores 3D surface points and free space locations calculated from line of sight data. The 3D surface points typically represent reflective surfaces detected by a sensor such as a LiDAR, a radar, a depth sensor or stereoscopic cameras. By using free space information, the system can unambiguously derive a movement or an intrusion the first time a surface is detected at a particular coordinate. Motion detection can be performed using a single frame or a single 3D point that was previously a free space location.

Abstract: We disclose systems and methods for object tracking which utilize a spectral response and a geometric aspect of a set of points. One method includes transmitting, with a multispectral lidar system, a multispectral light beam and analyzing a response, of a photodetector, to a return of the beam. The method also includes generating a point cloud with a set of points and determining a set of spectral responses of the set of points based on the analyzing of the response. The method also includes determining a set of material compositions for the set of points based on the set of spectral responses of the set of points. The method also includes grouping points in the set of points into groups based on both the set of material compositions and a geometric aspect of the set of points and creating one or more tracking object definitions using the groups.

Abstract: A method, system, and computer program product is provided for automatically configuring a detection device. The method includes scanning, with a LiDAR device, a region to generate LiDAR data, analyzing the LiDAR data to determine a material classification for the region, determining a zone of interest within the region based on the material classification, the zone of interest comprising a subset of the region defined by a spatial boundary, monitoring the zone of interest with the detection device, identifying an event occurring within the spatial boundary of the zone of interest based on monitoring the region with the detection device, and in response to identifying the event occurring within the spatial boundary, automatically initiating at least one responsive action.

Abstract: A method and apparatus of performing object detection on a path of travel is described. The invention is also related to obstacle detection on railway tracks. Object detection over irregular surfaces or traveling over know paths is also provided. The invention can be applied to railways for obstacle detection on train tracks with a look-ahead sensor system such as a lidar and/or camera system. The object detection may involve the use of multispectral lidar and material identification as well as artificial intelligence for object identification. A reference map is created during a first pass through a virtual tunnel of travel. A vehicle travelling through the tunnel of travel the vehicle will register with reference map and use differences between scans and the reference map to perform object detection. Responses are performed based on the object detection or object identification.

Abstract: A method, system, and computer program product is provided for automatically configuring a detection device. The method includes scanning, with a LiDAR device, a region to generate LiDAR data, analyzing the LiDAR data to determine a material classification for the region, determining a zone of interest within the region based on the material classification, the zone of interest comprising a subset of the region defined by a spatial boundary, monitoring the zone of interest with the detection device, identifying an event occurring within the spatial boundary of the zone of interest based on monitoring the region with the detection device, and in response to identifying the event occurring within the spatial boundary, automatically initiating at least one responsive action.

Abstract: We disclose systems and methods for object tracking which utilize a spectral response and a geometric aspect of a set of points. One method includes transmitting, with a multispectral lidar system, a multispectral light beam and analyzing a response, of a photodetector, to a return of the beam. The method also includes generating a point cloud with a set of points and determining a set of spectral responses of the set of points based on the analyzing of the response. The method also includes determining a set of material compositions for the set of points based on the set of spectral responses of the set of points. The method also includes grouping points in the set of points into groups based on both the set of material compositions and a geometric aspect of the set of points and creating one or more tracking object definitions using the groups.

Abstract: A method for detecting intrusions in a monitored volume in which: N tridimensional sensors acquire local point clouds in respective local coordinate systems, a central processing unit receives the acquired local point clouds and, for each sensor, computes updated tridimensional position and orientation of the sensor in a global coordinate system of the monitored volume by aligning a local point cloud acquired by said tridimensional sensor with a global tridimensional map of the monitored volume, and generates an aligned local point cloud on the basis of the updated tridimensional position and orientation of the sensor, the central processing unit monitors an intrusion in the monitored volume by comparing a free space of the aligned local point cloud with a free space of the global tridimensional map.

Abstract: We disclose sensor systems, and associated calibration systems and methods, that provide efficient and reliable depth and texture fusion. One disclosed method includes transmitting a first light beam from a first perspective, transmitting a second light beam from a second perspective, aligning a visible light photodetector with the second perspective, aligning a depth sensor with the first perspective, and mutually registering the visible light photodetector and the depth sensor using a return of the first light beam, a return of the second light beam, and a reference map. The reference map can include a transform from a reference frame based on the first perspective and a reference frame based on the second perspective.

Abstract: A method for detecting intrusions in a monitored volume in which: N tridimensional sensors acquire local point clouds in respective local coordinate systems; a central processing unit receives the acquired local point clouds and, for each sensor; computes updated tridimensional position and orientation of the sensor in a global coordinate system of the monitored volume by aligning a local point cloud acquired by the tridimensional sensor with a global tridimensional map of the monitored volume; and generates an aligned local point cloud on the basis of the updated tridimensional position and orientation of the sensor; the central processing unit monitors an intrusion in the monitored volume by comparing a free space of the aligned local point cloud with a free space of the global tridimensional map.

Abstract: A method for detecting intrusions in a monitored volume in which: N tridimensional sensors acquire local point clouds in respective local coordinate systems; a central processing unit receives the acquired local point clouds and, for each sensor; computes updated tridimensional position and orientation of the sensor in a global coordinate system of the monitored volume by aligning a local point cloud acquired by the tridimensional sensor with a global tridimensional map of the monitored volume; and generates an aligned local point cloud on the basis of the updated tridimensional position and orientation of the sensor; the central processing unit monitors an intrusion in the monitored volume by comparing a free space of the aligned local point cloud with a free space of the global tridimensional map.