Abstract: A proximity sensor includes first and second sensors disposed on a sensor body adjacent to one another. The first sensor is one of an emitter and a receiver. The second sensor is the other one of an emitter and a receiver. A third sensor is disposed adjacent the second sensor opposite the first sensor. The third sensor is an emitter if the first sensor is an emitter or a receiver if the first sensor is a receiver. Each sensor is positioned at an angle with respect to the other two sensors. Each sensor has a respective field of view. A first field of view intersects a second field of view defining a first volume that detects a floor surface within a first threshold distance. The second field of view intersects a third field of view defining a second volume that detects a floor surface within a second threshold distance.

Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.

Abstract: The present invention provides a mobile robot configured to navigate an operating environment, that includes a controller circuit that directs a drive of the mobile robot to navigate the mobile robot through an environment using camera-based navigation system and a camera including optics defining a camera field of view and a camera optical axis, where the camera is positioned within the recessed structure and is tilted so that the camera optical axis is aligned at an acute angle of above a horizontal plane in line with the top surface and is aimed in a forward drive direction of the robot body, and the camera is configured to capture images of the operating environment of the mobile robot.

Abstract: A robot configured to navigate a surface, the robot comprising a movement mechanism; a logical map representing data about the surface and associating locations with one or more properties observed during navigation; an initialization module configured to establish an initial pose comprising an initial location and an initial orientation; a region covering module configured to cause the robot to move so as to cover a region; an edge—following module configured to cause the robot to follow unfollowed edges; a control module configured to invoke region covering on a first region defined at least in part based at least part of the initial pose, to invoke region covering on least one additional region, to invoke edge-following, and to invoke region covering cause the mapping module to mark followed edges as followed, and cause a third region covering on regions discovered during edge-following.

Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.

Abstract: Vector Field SLAM is a method for localizing a mobile robot in an unknown environment from continuous signals such as WiFi or active beacons. Disclosed is a technique for localizing a robot in relatively large and/or disparate areas. This is achieved by using and managing more signal sources for covering the larger area. One feature analyzes the complexity of Vector Field SLAM with respect to area size and number of signals and then describe an approximation that decouples the localization map in order to keep memory and run-time requirements low. A tracking method for re-localizing the robot in the areas already mapped is also disclosed. This allows to resume the robot after is has been paused or kidnapped, such as picked up and moved by a user. Embodiments of the invention can comprise commercial low-cost products including robots for the autonomous cleaning of floors.

Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.

Abstract: A robot configured to navigate a surface, the robot comprising a movement mechanism; a logical map representing data about the surface and associating locations with one or more properties observed during navigation; an initialization module configured to establish an initial pose comprising an initial location and an initial orientation; a region covering module configured to cause the robot to move so as to cover a region; an edge-following module configured to cause the robot to follow unfollowed edges; a control module configured to invoke region covering on a first region defined at least in part based at least part of the initial pose, to invoke region covering on least one additional region, to invoke edge-following, and to invoke region covering cause the mapping module to mark followed edges as followed, and cause a third region covering on regions discovered during edge-following.

Abstract: A robotic cleaner includes a cleaning assembly for cleaning a surface and a main robot body. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and a width of the cleaning assembly is greater than a width of the main robot body. A robotic cleaning system includes a main robot body and a plurality of cleaning assemblies for cleaning a surface. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and each of the cleaning assemblies is detachable from the main robot body and each of the cleaning assemblies has a unique cleaning function.

Abstract: A robot configured to navigate a surface, the robot comprising a movement mechanism; a logical map representing data about the surface and associating locations with one or more properties observed during navigation; an initialization module configured to establish an initial pose comprising an initial location and an initial orientation; a region covering module configured to cause the robot to move so as to cover a region; an edge-following module configured to cause the robot to follow unfollowed edges; a control module configured to invoke region covering on a first region defined at least in part based at least part of the initial pose, to invoke region covering on least one additional region, to invoke edge-following, and to invoke region covering cause the mapping module to mark followed edges as followed, and cause a third region covering on regions discovered during edge-following.

Abstract: A robotic cleaner includes a cleaning assembly for cleaning a surface and a main robot body. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and a width of the cleaning assembly is greater than a width of the main robot body. A robotic cleaning system includes a main robot body and a plurality of cleaning assemblies for cleaning a surface. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and each of the cleaning assemblies is detachable from the main robot body and each of the cleaning assemblies has a unique cleaning function.

Abstract: A proximity sensor includes first and second sensors disposed on a sensor body adjacent to one another. The first sensor is one of an emitter and a receiver. The second sensor is the other one of an emitter and a receiver. A third sensor is disposed adjacent the second sensor opposite the first sensor. The third sensor is an emitter if the first sensor is an emitter or a receiver if the first sensor is a receiver. Each sensor is positioned at an angle with respect to the other two sensors. Each sensor has a respective field of view. A first field of view intersects a second field of view defining a first volume that detects a floor surface within a first threshold distance. The second field of view intersects a third field of view defining a second volume that detects a floor surface within a second threshold distance.

Abstract: A proximity sensor includes first and second sensors disposed on a sensor body adjacent to one another. The first sensor is one of an emitter and a receiver. The second sensor is the other one of an emitter and a receiver. A third sensor is disposed adjacent the second sensor opposite the first sensor. The third sensor is an emitter if the first sensor is an emitter or a receiver if the first sensor is a receiver. Each sensor is positioned at an angle with respect to the other two sensors. Each sensor has a respective field of view. A first field of view intersects a second field of view defining a first volume that detects a floor surface within a first threshold distance. The second field of view intersects a third field of view defining a second volume that detects a floor surface within a second threshold distance.

Abstract: A robot configured to navigate a surface, the robot comprising a movement mechanism; a logical map representing data about the surface and associating locations with one or more properties observed during navigation; an initialization module configured to establish an initial pose comprising an initial location and an initial orientation; a region covering module configured to cause the robot to move so as to cover a region; an edge-following module configured to cause the robot to follow unfollowed edges; a control module configured to invoke region covering on a first region defined at least in part based at least part of the initial pose, to invoke region covering on least one additional region, to invoke edge-following, and to invoke region covering cause the mapping module to mark followed edges as followed, and cause a third region covering on regions discovered during edge-following.

Abstract: Vector Field SLAM is a method for localizing a mobile robot in an unknown environment from continuous signals such as WiFi or active beacons. Disclosed is a technique for localizing a robot in relatively large and/or disparate areas. This is achieved by using and managing more signal sources for covering the larger area. One feature analyzes the complexity of Vector Field SLAM with respect to area size and number of signals and then describe an approximation that decouples the localization map in order to keep memory and run-time requirements low. A tracking method for re-localizing the robot in the areas already mapped is also disclosed. This allows to resume the robot after is has been paused or kidnapped, such as picked up and moved by a user. Embodiments of the invention can comprise commercial low-cost products including robots for the autonomous cleaning of floors.

Abstract: Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.

Abstract: Vector Field SLAM is a method for localizing a mobile robot in an unknown environment from continuous signals such as WiFi or active beacons. Disclosed is a technique for localizing a robot in relatively large and/or disparate areas. This is achieved by using and managing more signal sources for covering the larger area. One feature analyzes the complexity of Vector Field SLAM with respect to area size and number of signals and then describe an approximation that decouples the localization map in order to keep memory and run-time requirements low. A tracking method for re-localizing the robot in the areas already mapped is also disclosed. This allows to resume the robot after is has been paused or kidnapped, such as picked up and moved by a user. Embodiments of the invention can comprise commercial low-cost products including robots for the autonomous cleaning of floors.

Abstract: A robotic cleaner includes a cleaning assembly for cleaning a surface and a main robot body. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and a width of the cleaning assembly is greater than a width of the main robot body. A robotic cleaning system includes a main robot body and a plurality of cleaning assemblies for cleaning a surface. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and each of the cleaning assemblies is detachable from the main robot body and each of the cleaning assemblies has a unique cleaning function.

Abstract: A robot configured to navigate a surface, the robot comprising a movement mechanism; a logical map representing data about the surface and associating locations with one or more properties observed during navigation; an initialization module configured to establish an initial pose comprising an initial location and an initial orientation; a region covering module configured to cause the robot to move so as to cover a region; an edge-following module configured to cause the robot to follow unfollowed edges; a control module configured to invoke region covering on a first region defined at least in part based at least part of the initial pose, to invoke region covering on least one additional region, to invoke edge-following, and to invoke region covering cause the mapping module to mark followed edges as followed, and cause a third region covering on regions discovered during edge-following.