Abstract: An autonomous mobile device (AMD) uses sensors to explore a physical space and determine the locations of obstacles. Simultaneous localization and mapping (SLAM) techniques are used by the AMD to designate as keyframes some images and their associated descriptors of features in the space. Each keyframe indicates a location and orientation of the AMD relative to those features. Anchors are specified relative to keyframes. A marker is specified relative to one or more anchors. Because markers are associated with features in the physical space, they maintain their association with the physical space through various processes such as SLAM loop closures. Markers may specify locations in the physical space, such as navigation waypoints, navigation destinations such as a goal pose for exploring an unexplored area, as an observation target to facilitate exploration, and so forth. Markers may also be used to specify block listed locations to be avoided during exploration.

Abstract: A robotic assistant comprises a plurality of sensors on a mobile chassis. An occupancy map includes obstacle cost values for particular areas or cells of the map. These obstacle cost values may be based on whether an obstacle is detected and the confidence value of that detection, estimated precision of the location of the detected object, and so forth. A set of rules for preferred locations of robot movement is used to assess the occupancy map and to determine constraint cost value for the particular areas. For example, the area in a center of a hallway may be associated with a relatively high constraint cost value. An aggregate cost value may be calculated by summing the obstacle cost value and the constraint cost value for the particular area. The aggregate cost value may be used to determine a maximum permissible speed for the robot while traversing the particular area.