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: The novel technology described in this disclosure includes an example method comprising initializing an observability grid with an observation likelihood distribution for an environment being navigated by a mobile detection system, such as but not limited to a robot; searching the environment using the observability grid for an observation point; navigating, using a propulsion system, the robot to the observation point; and observing a target object from the observation point. The observability grid may include two or more spatial dimensions and an angular dimension. In some cases, the method may include sampling the environment with the robot based on the observation likelihood distribution of the observability grid.

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: Embodiments provide methods and apparatus for asynchronously classifying images provided by a robot. In a reconnaissance/exploratory or first cleaning pass, unidentified objects are avoided. Images of the object are uploaded over the Internet to a remote object detection and classification system, and the location is indicated by the cleaning robot. When the remote system subsequently returns an object identification or classification, the object can be indicated as something to be avoided, or the cleaning robot can return to the location and clean over the object if it is determined not to be a hazard. In one embodiment, the object is passed over at reduced speed or with a cleaning brush turned off.

Abstract: The novel technology described in this disclosure includes an example method comprising initializing an observability grid with an observation likelihood distribution for an environment being navigated by a mobile detection system, such as but not limited to a robot; searching the environment using the observability grid for an observation point; navigating, using a propulsion system, the robot to the observation point; and observing a target object from the observation point. The observability grid may include two or more spatial dimensions and an angular dimension. In some cases, the method may include sampling the environment with the robot based on the observation likelihood distribution of the observability grid.