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: 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: 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: 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: An information processing apparatus that executes processing for creating an environmental map includes a camera that photographs an image, a self-position detecting unit that detects a position and a posture of the camera on the basis of the image, an image-recognition processing unit that detects an object from the image, a data constructing unit that is inputted with information concerning the position and the posture of the camera and information concerning the object and executes processing for creating or updating the environmental map, and a dictionary-data storing unit storing dictionary data in which object information is registered. The image-recognition processing unit executes processing for detecting an object from the image with reference to the dictionary data. The data constructing unit applies the three-dimensional shape data to the environmental map and executes object arrangement on the environmental map.

Abstract: In a plane detection apparatus, a plane detection unit (3) includes a line fitting block (4) to select a group of distance data points being in one plane from distance data forming an image and extract lines from the distance data point group, and a region growing block (5) to detect one or more planar regions existing in the image from a group of all lines included in the image and extracted by the line fitting block (4). The line fitting block (4) first draws a line D1 connecting end points of the distance data point group, searches a point of interest brk whose distance to the line L1 is largest, segments the data point group by the point of interest brk when the distance is larger than a predetermined threshold, and determines a line L2 by the least-squares method when the distance is smaller than the predetermined threshold.

Abstract: An information processing apparatus that executes processing for creating an environmental map includes a camera that photographs an image, a self-position detecting unit that detects a position and a posture of the camera on the basis of the image, an image-recognition processing unit that detects an object from the image, a data constructing unit that is inputted with information concerning the position and the posture of the camera and information concerning the object and executes processing for creating or updating the environmental map, and a dictionary-data storing unit having stored therein dictionary data in which object information is registered. The image-recognition processing unit executes processing for detecting an object from the image acquired by the camera with reference to the dictionary data. The data constructing unit applies the three-dimensional shape data registered in the dictionary data to the environmental map and executes object arrangement on the environmental map.

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 having a signal sensor configured to measure a signal, a motion sensor configured to measure a relative change in pose, a local correlation component configured to correlate the signal with the position and/or orientation of the robot in a local region including the robot's current position, and a localization component configured to apply a filter to estimate the position and optionally the orientation of the robot based at least on a location reported by the motion sensor, a signal detected by the signal sensor, and the signal predicted by the local correlation component. The local correlation component and/or the localization component may take into account rotational variability of the signal sensor and other parameters related to time and pose dependent variability in how the signal and motion sensor perform. Each estimated pose may be used to formulate new or updated navigational or operational instructions for the robot.

Abstract: An environment map building method and an environment map building apparatus can express the surrounding embodiment with a high resolution in the height direction in a manner robust relative to observation noises.

Abstract: The present invention provides a position estimation apparatus capable of determining whether an estimated value deviates from an actual value and trying a process to correct the estimated value if the estimated value is determined to be incorrect. The position estimation apparatus employs a position prediction unit configured to produce a prediction of the position of a mobile object having an odometry sensor mounted thereon, an environment observation unit configured to keep track of each feature point in the environment of the mobile object, a prediction-error check unit configured to determine whether the position prediction produced by the position prediction unit is correct or incorrect, a position-prediction correction unit configured to correct a wrong position prediction and a position/posture updating unit configured to update the position and/or posture of the mobile object on the basis of a correct position prediction.

Abstract: An environment recognizing device and an environment recognizing method can draw an environment map for judging if it is possible to move a region where one or more than one steps are found above or below a floor, a route planning device and a route planning method that can appropriately plan a moving route, using such an environment map and a robot equipped with such an environment recognizing device and a route planning device.

Abstract: The present invention provides an obstacle avoiding apparatus, an obstacle avoiding method, an obstacle avoiding program, and a mobile robot apparatus that can accurately model a robot apparatus and plan a highly precise moving route for the robot apparatus that avoids obstacles.

Abstract: An obstacle recognition apparatus is provided which can recognize an obstacle by accurately extracting a floor surface. It includes a distance image generator (222) to produce a distance image using a disparity image and homogeneous transform matrix, a plane detector (223) to detect plane parameters on the basis of the distance image from the distance image generator (222), a coordinate transformer (224) to transform the homogeneous transform matrix into a coordinate of a ground-contact plane of a robot apparatus (1), and a floor surface detector (225) to detect a floor surface using the plane parameters from the plane detector (223) and result of coordinate transformation from the coordinate transformer (224) and supply the plane parameters to an obstacle recognition block (226).

Abstract: The present invention provides a position estimation apparatus capable of determining whether an estimated value deviates from an actual value and trying a process to correct the estimated value if the estimated value is determined to be incorrect. The position estimation apparatus employs a position prediction unit configured to produce a prediction of the position of a mobile object having an odometry sensor mounted thereon, an environment observation unit configured to keep track of each feature point in the environment of the mobile object, a prediction-error check unit configured to determine whether the position prediction produced by the position prediction unit is correct or incorrect, a position-prediction correction unit configured to correct a wrong position prediction and a position/posture updating unit configured to update the position and/or posture of the mobile object on the basis of a correct position prediction.

Abstract: In a plane detection apparatus, a plane detection unit (3) includes a line fitting block (4) to select a group of distance data points being in one plane from distance data forming an image and extract lines from the distance data point group, and a region growing block (5) to detect one or more planar regions existing in the image from a group of all lines included in the image and extracted by the line fitting block (4). The line fitting block (4) first draws a line D1 connecting end points of the distance data point group, searches a point of interest brk whose distance to the line L1 is largest, segments the data point group by the point of interest brk when the distance is larger than a predetermined threshold, and determines a line L2 by the least-squares method when the distance is smaller than the predetermined threshold.

Abstract: A self-localization system uses both of a global search apparatus, which is based on grid-based Markov localization, and a local search apparatus, which uses an extended Kalman filter. If an observation result by the global search apparatus is valid, then updating of an observation result by the local search apparatus is permitted, but if the observation result is not valid, then updating of the observation result by the local search apparatus is not performed. On the other hand, if the observation result by the local search apparatus is valid, then a state of the local search is outputted, but if the observation result is not valid, then the local search apparatus is re-initialized. Accordingly, the self-localization of a robot can be performed based on sensor information of the robot and motion information performed by the robot in an environment including artificial landmarks.

Abstract: The present invention provides an obstacle avoiding apparatus, an obstacle avoiding method, an obstacle avoiding program, and a mobile robot apparatus that can accurately model a robot apparatus and plan a highly precise moving route for the robot apparatus that avoids obstacles.

Abstract: An environment identifying apparatus (400) is adapted to be mounted in a robot apparatus that moves in an identifiable unique environment in which a plurality of landmarks are located so as to identify the current environment by means of a plurality of registered environments.

Abstract: An environment map building method and an environment map building apparatus can express the surrounding embodiment with a high resolution in the height direction in a manner robust relative to observation noises.