Abstract: Methods, systems, and apparatus for drone-assisted sensor mapping are disclosed. A method includes detecting a sensor in a detection area of a drone; based on detecting the sensor in the detection area of the drone, detecting the drone in sensor data captured by the sensor; determining a detection area of the sensor based on movement of the drone after the drone is detected; and determining a destination for the drone based on the detection area of the sensor. The method may include mapping boundaries of the detection area of the sensor to a map of an area where the sensor is located. The sensor can be a passive infrared sensor, an active infrared sensor, a radar sensor, a sonar sensor, a time of flight sensor, a structured light sensor, or a lidar sensor.

Abstract: Methods, systems, and apparatus for drone navigation within a property. A method includes detecting an obstacle in a navigation path of a drone, determining a classification of the obstacle, determining whether to temporarily land based on the classification of the obstacle, and temporarily landing the drone until the obstacle clears the navigation path of the drone.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for performing automated mapping of sensors at a location of a property. A monitoring server of a system for monitoring a property obtains mapping information that indicates navigable areas at the property. A drone that communicates with the monitoring server is used to navigate the property. In response to the drone navigating the property, sensors and their respective location at each navigable areas are identified based on the mapping information. The monitoring server associates sensors at each area with a corresponding location of the sensor in a data model of the property. Labels descriptive of the respective sensors are generated based on the location of the identified sensors. The monitoring server determines a mapping of a label to a respective sensor associated with the data model of the property.

Abstract: Methods, systems, and apparatus for drone landing ground station. A method includes determining that a drone is landing on a ground station, based on determining that the drone is landing on the ground station, determining a magnetic field to generate at a first magnetic component at a first position in the ground station and an opposing magnetic polar at a second magnetic component at a second position in the ground station, and generating the magnetic field at the first magnetic component and the opposing magnetic field at the second magnetic component.

Abstract: Methods, systems, and apparatus a drone for installing sensors. A method includes determining to emulate a view of a camera at a particular location with a drone, deploying the drone to the particular location, obtaining an image captured by a drone, and emulating the view of the camera with the image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for navigation using planar landmarks. In some implementations, images depicting an area of a property captured by a camera are obtained. Landmarks in the area are identified based on the images. An expected stability for each of the landmarks are determined. A map for the area is generated based on the expected stability for each of the landmarks. The map is transmitted to one or more electronic devices.

Abstract: Techniques are described for an autonomous asset management system that integrates autonomous devices, such as drone devices and other robotic devices, with a home security system of a property to enable management, monitoring, and/or tracking of various assets located within the property. In some implementations, an indication of an asset associated with a property is obtained by an autonomous device. Sensor data collected by one or more sensors of the property is obtained by the autonomous device based on the indication of the asset. A present status of the asset is determined by the autonomous device based on the sensor data. A determination that the present status of the asset does not correspond to an expected status of the asset is made by the autonomous device. In response, the autonomous device navigates to the particular location of the property.

Abstract: Techniques are described for enabling a drone device to use a dynamic multi-dimensional spatial representation of an indoor property environment to improve autonomous navigation. In some implementations, an instruction to perform an action at a particular location of a property is received by a drone device. A spatial representation of the property that identifies a dynamic object is obtained by the drone device. The status of the dynamic object impacts an ability of the drone device to navigate near the dynamic object. Sensor data collected by one or more sensors of a monitoring system of the property and that indicates a present status of the dynamic object is obtained by the drone device. A path to the particular location is determined by the drone device. The path to the particular location is finally navigated by the drone device.

Abstract: Techniques are described for enabling a drone device to use a dynamic multi-dimensional spatial representation of an indoor property environment to improve autonomous navigation. In some implementations, an instruction to perform an action at a particular location of a property is received by a drone device. A spatial representation of the property that identifies a dynamic object is obtained by the drone device. The status of the dynamic object impacts an ability of the drone device to navigate near the dynamic object. Sensor data collected by one or more sensors of a monitoring system of the property and that indicates a present status of the dynamic object is obtained by the drone device. A path to the particular location is determined by the drone device. The path to the particular location is finally navigated by the drone device.

Abstract: Techniques are described for an autonomous asset management system that integrates autonomous devices, such as drone devices and other robotic devices, with a home security system of a property to enable management, monitoring, and/or tracking of various assets located within the property. In some implementations, an indication of an asset associated with a property is obtained by an autonomous device. Sensor data collected by one or more sensors of the property is obtained by the autonomous device based on the indication of the asset. A present status of the asset is determined by the autonomous device based on the sensor data. A determination that the present status of the asset does not correspond to an expected status of the asset is made by the autonomous device. In response, the autonomous device navigates to the particular location of the property.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a storage device, for generating a three-dimensional map of a property. The method includes storing at least a portion of an initial map modification data structure, receiving an instruction that instructs the robotic device to initiate property mapping, obtaining image data describing a portion of the property that is mounted to the robotic device, analyzing the obtained image data to determine whether the image data depicts a marker, in response to a determination that the obtained image data depicts a marker, determining the pose of the camera that is mounted to the robotic device, updating the initial map modification data structure using the pose of the camera that is mounted to the robotic device, obtaining an initial three-dimensional map of the property; and modifying the initial three-dimensional map of the property based on the updated map modification data structure.

Abstract: Techniques are described for an autonomous asset management system that integrates autonomous devices, such as drone devices and other robotic devices, with a home security system of a property to enable management, monitoring, and/or tracking of various assets located within the property. In some implementations, an indication of an asset associated with a property is obtained by an autonomous device. Sensor data collected by one or more sensors of the property is obtained by the autonomous device based on the indication of the asset. A present status of the asset is determined by the autonomous device based on the sensor data. A determination that the present status of the asset does not correspond to an expected status of the asset is made by the autonomous device. In response, the autonomous device navigates to the particular location of the property.

Abstract: Techniques are described for enabling a drone device to use a dynamic multi-dimensional spatial representation of an indoor property environment to improve autonomous navigation. In some implementations, an instruction to perform an action at a particular location of a property is received by a drone device. A spatial representation of the property that identifies a dynamic object is obtained by the drone device. The status of the dynamic object impacts an ability of the drone device to navigate near the dynamic object. Sensor data collected by one or more sensors of a monitoring system of the property and that indicates a present status of the dynamic object is obtained by the drone device. A path to the particular location is determined by the drone device. The path to the particular location is finally navigated by the drone device.