Alarm.com Incorporated

Alarm.com Incorported

Ahmad Seyfi

Babak Rezvani

Donald Gerard Madden

Glenn Tournier

Timon Meyer

Daniel Todd Kerzner

Gang Qian

Ethan Shayne

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.

Asset management monitoring

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.

Automated mapping of sensors at a location

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.

Drone navigation and landing

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for lighting adaptive navigation. In some implementations, a method includes receiving map data associated with a property; obtaining sensor data; based on the map data and the sensor data, determining a lighting scenario; and based on the lighting scenario, configuring the robotic device.

Lighting adaptive navigation

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for drone-assisted thermal monitoring. One of the methods includes determining a first temperature measurement at a first location of a property, navigating from the first location to a second location of the property, determining a second temperature measurement at the second location, generating a thermal model for the property based on the first temperature measurement and the second temperature measurement, and providing the thermal model for output.

Drone-assisted thermal monitoring techniques

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for receiving a request to deploy an aerial drone to assist an emergency vehicle from a first location to a second location; determining a route to be traversed by the emergency vehicle from the first location to the second location based on the request; and deploying the aerial drone to traverse the route in advance of the emergency vehicle.

Drone first responder assistance

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.

Dynamic drone navigation

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for drones. In some implementations, a method may include obtaining an image of an electrical device; determining a power source of the electrical device based on the image of the electrical device; determining whether the power source of the electrical device is capable of charging a drone based on the image of the electrical device; and based on determining that the power source of the electrical device is capable of charging the drone based on the image of the electrical device, charging the drone with the power source.

Base station-less drones

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.

Drone landing ground station with magnetic fields

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining that current data captured at a current location of a drone satisfies localization adjustment criteria; in response to determining that the current data captured at the current location of the drone satisfies the localization adjustment criteria, identifying previously captured image data; determining a previous expected location of the drone based on both an expected change in location of the drone and a first previous location determined from other image data captured before the previously captured image data; determining a location difference between the previous expected location of the drone and a second previous location determined from the previously captured image data; and determining the current location of the drone based on the location difference.

Robot localization

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for a mobile docking station. In some implementations, a method for a mobile docking station includes receiving a service request from a first user; determining assignment details based on the service request; determining a plurality of devices to send to a location based on the assignment details; deploying the plurality of devices to the location; receiving data from a first device of the plurality of devices; based on the data, scheduling a pickup of the first device; and deploying a second device for the pickup of the first device.

Mobile docking station

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.

Drone-assisted sensor mapping

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.

Robot sensor installation

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.

Navigation using selected visual landmarks

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for lighting adaptive navigation. In some implementations, map data associated with a property is received. Sensor data is obtained. Based on the map data and the sensor data, a lighting scenario is determined. Based on the lighting scenario, a modification to at least one of the lighting scenario, to a planned navigation path for the robotic device, to settings for a sensor of the robotic device, to a position for a sensor of the robotic device, or to a position of the robotic device is determined. An action is performed by based on the one or more modifications.

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Tysons, VA, United States of America

Ahmad Seyfi