Abstract: In one embodiment, a user indicates one or more virtual zones on an area map on a user device for a particular robot. The zones are then transferred to the robot. The robot determines an optimum order for multiple zones and a path for navigating to the different zones.

Abstract: In one embodiment, a cleaning robot stores multiple floorplans. The robot automatically determines which floorplan it is in by localizing and trying to match its detected environment to the stored map. The best fit is the map for the current floor. If there is no match above a confidence threshold, the robot assumes it is a new floor or the floorplan has changed (e.g., furniture has moved), and the robot initiates a discovery mode to map the floorplan and add it to the robot's memory.

Abstract: In one embodiment, a virtual boundary is provided in the global coordinates of the area map and is converted into a plurality of line segments corresponding to a plurality of partial maps. In one embodiment, a physical boundary indicator is used during a training/mapping run, with the location added to the area map and the physical boundary indicator later moved. In one embodiment, the virtual boundary changes over time to change cleaning areas, act as a gate, change associated cleaning mode, etc. In one embodiment, virtual areas with boundaries are selected by a user.

Abstract: In one embodiment, a user indicates one or more virtual zones on an area map on a user device for a particular robot. The zones are then transferred to the robot. The robot determines an optimum order for multiple zones and a path for navigating to the different zones.

Abstract: In one embodiment, a cleaning robot stores multiple floorplans. The robot automatically determines which floorplan it is in by localizing and trying to match its detected environment to the stored map. The best fit is the map for the current floor. If there is no match above a confidence threshold, the robot assumes it is a new floor or the floorplan has changed (e.g., furniture has moved), and the robot initiates a discovery mode to map the floorplan and add it to the robot's memory.

Abstract: In one embodiment, a virtual boundary is provided in the global coordinates of the area map and is converted into a plurality of line segments corresponding to a plurality of partial maps. In one embodiment, a physical boundary indicator is used during a training/mapping run, with the location added to the area map and the physical boundary indicator later moved. In one embodiment, the virtual boundary changes over time to change cleaning areas, act as a gate, change associated cleaning mode, etc. In one embodiment, virtual areas with boundaries are selected by a user.

Abstract: Embodiments provide methods and apparatus for effectively using signal strength and other data from a robot to optimize robot operation. In one embodiment, the cleaning robot can interact with other home controllers over a network to optimize the operation of the cleaning robot. In one embodiment, the cleaning robot measures a variety of data as it travels through a space, and generates a map (e.g., a heat map). The data is provided in different layers for easy display and selection by a user. In one embodiment, the cleaning robot can act as a hub for communicating with other home controllers and coordinating actions.