Abstract: A method for generating guidance information is disclosed, which uses one or more machine learning algorithms to continually adapt and update a version of a model used to generate guidance instructions based on feedback data received from one or more users, such that the instructions generated by the model better fit the expectations or behaviour of the user or users. The method can be performed on a mobile navigation device, such that the model is adjusted to suit the needs of a single user. Alternatively, the method can be performed on a server based on feedback data from a plurality of users, and the updated model, once generated, transmitted to a plurality of mobile navigation devices to replace the existing model.

Abstract: A method for generating guidance information is disclosed, which uses one or more machine learning algorithms to continually adapt and update a version of a model used to generate guidance instructions based on feedback data received from one or more users, such that the instructions generated by the model better fit the expectations or behaviour of the user or users. The method can be performed on a mobile navigation device, such that the model is adjusted to suit the needs of a single user. Alternatively, the method can be performed on a server based on feedback data from a plurality of users, and the updated model, once generated, transmitted to a plurality of mobile navigation devices to replace the existing model.

Abstract: Described herein are technologies pertaining to autonomously docking a mobile robot at a docking station for purposes of recharging batteries of the mobile robot. The mobile robot uses vision-based navigation and a known map of the environment to navigate toward the docking station. Once sufficiently proximate to the docking station, the mobile robot captures infrared images of the docking station, and granularly aligns itself with the docking station based upon the captured infrared images of the docking station. As the robot continues to drive towards the docking station, the robot monitors infrared sensors for infrared beams emitted from the docking station. If the infrared sensors receive the infrared beams, the robot continues to drive forward until the robot successfully docks with the docking station.

Abstract: Described herein are technologies pertaining to autonomously docking a mobile robot at a docking station for purposes of recharging batteries of the mobile robot. The mobile robot uses vision-based navigation and a known map of the environment to navigate toward the docking station. Once sufficiently proximate to the docking station, the mobile robot captures infrared images of the docking station, and granularly aligns itself with the docking station based upon the captured infrared images of the docking station. As the robot continues to drive towards the docking station, the robot monitors infrared sensors for infrared beams emitted from the docking station. If the infrared sensors receive the infrared beams, the robot continues to drive forward until the robot successfully docks with the docking station.