Abstract: An autonomous cleaning robot (e.g., an autonomous vacuum) may clean an environment using a cleaning head that is self-actuated. The cleaning head includes an actuator assembly comprising an actuator configured to control rotation and vertical movement of a cleaning roller, a controller, and a cleaning roller having an elongated cylindrical length connected to the actuator assembly. The cleaning head also includes a computer processor connected to the actuator assembly and a non-transitory computer-readable storage medium that causes the computer processor to map the environment based on sensor data captured by the autonomous vacuum. The computer processor may determine an optimal height for the cleaning head based on the map and instruct the actuator assembly to adjust the height of the cleaning head.

Abstract: An autonomous cleaning robot (e.g., an autonomous vacuum) may clean an environment using a cleaning head that is self-actuated. The cleaning head includes an actuator assembly comprising an actuator configured to control rotation and vertical movement of a cleaning roller, a controller, and a cleaning roller having an elongated cylindrical length connected to the actuator assembly. The cleaning head also includes a computer processor connected to the actuator assembly and a non-transitory computer-readable storage medium that causes the computer processor to map the environment based on sensor data captured by the autonomous vacuum. The computer processor may determine an optimal height for the cleaning head based on the map and instruct the actuator assembly to adjust the height of the cleaning head.

Abstract: An autonomous vacuum implements a semi-waterproof waste bag capable of collecting dry waste from vacuum debris and liquid waste from mopping. The autonomous vacuum leverages a dual-roller cleaning head, one for dry cleaning and another for wet cleaning. The autonomous vacuum utilizes vacuum force to ingest both dry waste and liquid waste from the cleaning head into the semi-waterproof waste bag. The semi-waterproof waste bag includes a non-permeable portion formed of a waterproof material and a permeable portion formed of an air-permeable material. The semi-waterproof waste bag may further include a water-absorbent material, e.g., water-absorbing spherical beads.

Abstract: A muffler for an autonomous vacuum includes one or more chambers and one or more noise-absorbing elements for noise reduction of air exhausted into an external environment of the autonomous vacuum. The muffler is coupled to a vacuum stack inclusive of a vacuum motor. The muffler includes a main body, a foam layer, and a sealing plate. The main body includes an inlet for air exhausted by the vacuum motor and forms the one or more chambers fluidically connected to the inlet. The foam layer is disposed within one of the chambers of the main body. The foam layer absorbs sound waves incident on the foam layer. The sealing plate is affixed to the main body and includes an outlet to exhaust air from the chambers to an external environment of the autonomous vacuum.

Abstract: An autonomous vacuum leverages a dual-roller cleaning head, one for dry cleaning and another for wet cleaning. The autonomous vacuum utilizes vacuum force to ingest both dry waste and liquid waste from the cleaning head into the waste bag. The autonomous vacuum further comprises a cleaning head coupled to the vacuum motor, the cleaning head forming a mop roller cavity including a first end and a second end opposite the first end, wherein a mop opening exposes the mop roller cavity to an external environment. The cleaning head comprises a mop motor positioned at the first end of the mop roller cavity and including a driver clutch. The cleaning head further comprises mop roller core having a first end, a second end opposite to the first end, and an outer surface covered with a fabric material, the mop roller comprising a spring clutch positioned at the first end of the mop roller and removably couplable to the driver clutch of the mop motor.

Abstract: A method for recognizing persons in video streams includes obtaining a live video stream, detecting a first person in the live video stream, determining from analysis of the live video stream first information that identifies an attribute of the first person, determining based on at least some of the first information that the first person is not identifiable to the computing system, storing at least some of the first information, receiving a user classification of the first person as being a stranger, and deleting the stored first information.

Abstract: A method for recognizing persons in video streams includes obtaining a live video stream, detecting a first person in the live video stream, determining from analysis of the live video stream first information that identifies an attribute of the first person, determining based on at least some of the first information that the first person is not identifiable to the computing system, storing at least some of the first information, receiving a user classification of the first person as being a stranger, and deleting the stored first information.

Abstract: The various embodiments described herein include methods, devices, and systems for providing event alerts. In one aspect, a method includes obtaining a video feed. A frame of the video feed is analyzed at a first resolution to determine whether the frame includes a potential instance of a person. In accordance with the determination that the image includes the potential instance, a region is denoted around the potential instance. The region is analyzed at a second resolution, greater than the first resolution. In accordance with a determination that the region includes the instance of the person. a determination that the frame includes the person is made. An indication of the determination is stored for use in subsequent alert notification processing.

Abstract: Systems and methods for navigating an autonomous vacuum are disclosed. According to one method, the autonomous vacuum traverses a cleaning environment having a plurality of surfaces. As the autonomous vacuum is traversing the cleaning environment, sensors on the autonomous vacuum capture sensor data describing a first section of a surface on which the autonomous vacuum is currently traversing. Based on the received sensor data, the autonomous vacuum can determine that the first section is of a first surface type of a plurality of surface types. The autonomous vacuum can generate a user interface with a background displaying the determined first surface type to notify the user of where the autonomous vacuum is cleaning.

Abstract: A computing system obtains a video feed. For a frame of the video feed, the computing system analyzes the frame to determine whether the frame includes a potential instance of an event. In accordance with a determination that the frame includes the potential instance of an event, the computing system determines for the event an event category from a plurality of predefined event categories. It stores an indication of the event category. It determines whether the event category matches a predefined notification filter definition. In accordance with a determination that the event category matches the predefined notification filter definition, the computing system issues an alert notification to a user client device. In accordance with a determination that the event category does not match the predefined notification filter definition, the computing system refrains from issuing the alert notification.

Abstract: A method for recognizing persons in video streams includes obtaining a live video stream, detecting a first person in the live video stream, determining from analysis of the live video stream first information that identifies an attribute of the first person, determining based on at least some of the first information that the first person is not identifiable to the computing system, storing at least some of the first information, receiving a user classification of the first person as being a stranger, and deleting the stored first information.

Abstract: The various implementations described herein include systems and methods for recognizing persons in video streams. In one aspect, a method includes: (1) obtaining a live video stream; (2) detecting person(s) in the stream; and (3) determining, from analysis of the live video stream, personally identifiable information of the detected person(s); (4) determining, based on the personally identifiable information, that the first person is not known to the computing system; (5) in accordance with the determination that the first person is not known: (a) storing the personally identifiable information; and (b) requesting a user to classify the first person; and (6) in accordance with (i) a determination that a predetermined amount of time has elapsed since the request was transmitted and a response was not received, or (ii) a determination that a response was received classifying the first person as a stranger, deleting the stored personally identifiable information.

Abstract: A method for recognizing persons in video streams includes obtaining a live video stream, detecting a first person in the live video stream, determining from analysis of the live video stream first information that identifies an attribute of the first person, determining based on at least some of the first information that the first person is not identifiable to the computing system, storing at least some of the first information, receiving a user classification of the first person as being a stranger, and deleting the stored first information.

Abstract: The various implementations described herein include systems and methods for recognizing persons in video streams. In one aspect, a method includes: obtaining images collected by video cameras in a smart home environment, each image including a detected person; for each image, obtaining first information that identifies an attribute of the detected person, the first information generated from analysis of the image; grouping the images into a first group of a plurality of groups based on the first information, each group of the plurality of groups representing a unique person; receiving a request to remove a first image from the first group; removing the first image from the first group; and disassociating the first information from the first group.

Abstract: An autonomous cleaning robot (e.g., an autonomous vacuum) may clean an environment using a cleaning head that is self-actuated. The cleaning head includes an actuator assembly comprising an actuator configured to control rotation and vertical movement of a cleaning roller, a controller, and a cleaning roller having an elongated cylindrical length connected to the actuator assembly. The cleaning head also includes a computer processor connected to the actuator assembly and a non-transitory computer-readable storage medium that causes the computer processor to map the environment based on sensor data captured by the autonomous vacuum. The computer processor may determine an optimal height for the cleaning head based on the map and instruct the actuator assembly to adjust the height of the cleaning head.

Abstract: An autonomous cleaning robot (e.g., an autonomous vacuum) may use a sensor system to map an environment that may be used to determine where to clean. The autonomous vacuum receives visual data about the environment and determines a ground plane of the environment based on the visual data. The autonomous vacuum detects objects within the environment based on the ground plane. For each object, the autonomous vacuum segments a three-dimensional (3D) representation of the object out of the visual data and determines whether the object is static or dynamic. The autonomous vacuum adds static objects to a long-term level of a map of the environment and dynamic objects to an intermediate level of the map. The autonomous vacuum may further add virtual borders, flags, walls, and messes to the map.

Abstract: A method includes obtaining from an image sensor of a video camera a primary real-time video stream comprising images of a field of view of the video camera; identifying from the primary video stream one or more regions of interest in the field of view of the video camera; while obtaining the primary video stream, creating a first video sub-stream comprising a first plurality of images for a first one of the one or more identified regions of interest, wherein: images of the first plurality of images include image data for portions of the field of the video camera that include the first identified region of interest, and the images of the first plurality of images have fields of view that are smaller than the field of view of the video camera; and providing the first video sub-stream for display at a client device.

Abstract: A computing system obtains a video feed. For a frame of the video feed, the computing system analyzes the frame to determine whether the frame includes a potential instance of an event. In accordance with a determination that the frame includes the potential instance of an event, the computing system determines for the event an event category from a plurality of predefined event categories. It stores an indication of the event category. It determines whether the event category matches a predefined notification filter definition. In accordance with a determination that the event category matches the predefined notification filter definition, the computing system issues an alert notification to a user client device. In accordance with a determination that the event category does not match the predefined notification filter definition, the computing system refrains from issuing the alert notification.

Abstract: A method for recognizing persons in video streams includes obtaining a live video stream, detecting a first person in the live video stream, determining from analysis of the live video stream first information that identifies an attribute of the first person, determining based on at least some of the first information that the first person is not identifiable to the computing system, storing at least some of the first information, receiving a user classification of the first person as being a stranger, and deleting the stored first information.