Abstract: Systems and method of the present invention provide for one or more server computers configured to register a domain name; receive a request to: generate a file folder linked to an online storage account owned by a user; and map a URL, comprising a sub domain concatenated to the registered domain name, to the file folder. The server(s) may be further configured to determine whether an alias for the URL, comprising the subdomain, is located in a DNS record for the domain name. The server(s) may automatically generate the file folder and map the URL to the file folder. Any HTTP requests comprising the URL received by the server(s) may be resolved to the file folder.

Abstract: Systems and method of the present invention provide for one or more server computers configured to register a domain name; receive a request to: generate a file folder linked to an online storage account owned by a user; and map a URL, comprising a sub domain concatenated to the registered domain name, to the file folder. The server(s) may be further configured to determine whether an alias for the URL, comprising the subdomain, is located in a DNS record for the domain name. The server(s) may automatically generate the file folder and map the URL to the file folder. Any HTTP requests comprising the URL received by the server(s) may be resolved to the file folder.

Abstract: A mobile robot system is provided that includes a docking station having at least two pose-defining fiducial markers. The pose-defining fiducial markers have a predetermined spatial relationship with respect to one another and/or to a reference point on the docking station such that a docking path to the base station can be determined from one or more observations of the at least two pose-defining fiducial markers. A mobile robot in the system includes a pose sensor assembly. A controller is located on the chassis and is configured to analyze an output signal from the pose sensor assembly. The controller is configured to determine a docking station pose, to locate the docking station pose on a map of a surface traversed by the mobile robot and to path plan a docking trajectory.

Abstract: Simultaneous localization and mapping (SLAM) utilizes multiple view feature descriptors to robustly determine location despite appearance changes that would stifle conventional systems. A SLAM algorithm generates a feature descriptor for a scene from different perspectives using kernel principal component analysis (KPCA). When the SLAM module subsequently receives a recognition image after a wide baseline change, it can refer to correspondences from the feature descriptor to continue map building and/or determine location. Appearance variations can result from, for example, a change in illumination, partial occlusion, a change in scale, a change in orientation, change in distance, warping, and the like. After an appearance variation, a structure-from-motion module uses feature descriptors to reorient itself and continue map building using an extended Kalman Filter.

Abstract: Simultaneous localization and mapping (SLAM) utilizes multiple view feature descriptors to robustly determine location despite appearance changes that would stifle conventional systems. A SLAM algorithm generates a feature descriptor for a scene from different perspectives using kernel principal component analysis (KPCA). When the SLAM module subsequently receives a recognition image after a wide baseline change, it can refer to correspondences from the feature descriptor to continue map building and/or determine location. Appearance variations can result from, for example, a change in illumination, partial occlusion, a change in scale, a change in orientation, change in distance, warping, and the like. After an appearance variation, a structure-from-motion module uses feature descriptors to reorient itself and continue map building using an extended Kalman Filter.