Provided are a mobile body, an information processing method, and a computer program. A mobile body of the present disclosure includes: an imaging unit configured to capture an image of an environment around the mobile body; an estimation unit configured to estimate a position of the mobile body on the basis of the image captured by the imaging unit; a calculation unit configured to calculate the position of the mobile body on the basis of a control command for controlling movement of the mobile body; and a wind information calculation unit configured to calculate information regarding wind acting on the mobile body on the basis of a first position that is the position of the mobile body, which is estimated by the estimation unit, and a second position that is the position of the mobile body, which is calculated by the calculation unit.

A method of localizing a mobile robot 100 with respect to a target object 601 using an initial map of a reference object which is a representation of the target object is disclosed herein. The method comprises obtaining LiDAR data 503 of the target object 601 captured by a LiDAR device 203 of the mobile robot 100 as the mobile robot 100 traverses in an environment associated with the target object 601 the LiDAR data including respective point cloud representations of the target object 501 and the environment in various sampling instances; iteratively updating pose data representing estimated pose of the mobile robot 100 with respect to a known reference location in corresponding sampling instances as the mobile robot traverses the environment; extracting a subset of LiDAR data points in the point cloud representation of a previous sampling instance, the subset of LiDAR data points corresponding to features of the target object 601 in the initial map based on the estimated pose of the mobile robot 100 associated with the previous sampling instance; obtaining desired LiDAR data points in the point cloud representation in a current sampling instance, the desired LiDAR data points including current LiDAR data points which correspond to the extracted subset of LiDAR data points in the previous sampling instance; and determining a localization pose of the mobile robot 100 with respect to the target object 601 in the current sampling instance based on the desired LiDAR data points. A system for localizing a mobile robot is also disclosed herein.

A system and method are described that provide for queueing robot operations in a warehouse environment based on workflow optimization instructions. In one example of the system/method of the present invention, a control system causes certain robots to queue proximate to one another to permit resources to be obtained, transported, deposited, etc. without the robots crashing into one another (or into other objects), or forming traffic jams. A robot may remain at an assigned queue position at least until another position assigned to the robot becomes available.

A system and method are described that provide for mapping features of a warehouse environment having improved workflow. In one example of the system/method of the present invention, a mapping robot is navigated through a warehouse environment, and sensors of the mapping robot collect geospatial data as part of a mapping mode. A Frontend N block of a map framework may be responsible for reading and processing the geospatial data from the sensors of the mapping robot, as well as various other functions. The data may be stored in a keyframe object at a keyframe database. A Backend block of the map framework may be useful for detecting loop constraints, building submaps, optimizing a pose graph using keyframe data from one or more trajectory blocks, and/or various other functions.

A vehicle system (1) switches control between a restart period after restart of a function of controlling traveling of the vehicle following a parking period during which the function is stopped, until the vehicle moves and first detects a magnetic marker and a normal travel period after the vehicle detects the magnetic marker following the restart period. In the restart period, restart control (S105) is performed in which a position of the vehicle is identified based on a position measured in the restart period to cause the vehicle to travel. In the normal travel period, normal travel control (S107) is performed in which the position of the vehicle is identified based on a position of the detected magnetic marker to cause the vehicle to travel.

A vehicle for an automated storage and retrieval system is configured to follow a route relative to tracks of the automated storage and retrieval system. The route includes one or more track crossings. The vehicle includes a first set of wheels capable of moving the vehicle in a first direction; a second set of wheels capable of moving the vehicle in a second direction perpendicular to the first direction; and one or more sensors attached to the vehicle and configured to detect the one or more track crossings while the vehicle is moving in the first direction or the second direction.

A system and method are described that provide for queueing robot operations in a warehouse environment based on workflow optimization instructions. In one example of the system/method of the present invention, a control system causes certain robots to queue proximate to one another to permit resources to be obtained, transported, deposited, etc. without the robots crashing into one another (or into other objects), or forming traffic jams. A robot may remain at an assigned queue position at least until another position assigned to the robot becomes available.

A mobile body controller according to the present disclosure includes circuitry configured to recognize an environment surrounding a mobile body to be controlled, and change parameters used for self-position estimation by the mobile body based on the recognized environment.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for improving visual inertial odometry (VIO). One of the methods includes identifying two or more parameters of a robot; generating, using the two or more parameters, a multi-dimensional space; generating two or more configurations for the robot by sampling the multi-dimensional space; determining, for each of the two or more configurations, a visual inertial odometry (VIO) trajectory; generating, for each of the trajectories using the corresponding trajectory and a ground truth trajectory, (i) error data representing a difference of the corresponding trajectory from the ground truth trajectory and (ii) processing data representing processing metrics from the determination of the corresponding trajectory; selecting, using (i) the error data and (ii) the processing data, a configuration of the two or more configurations; and providing, to the robot, the selected configuration for navigating an area.

A system and method are described that provide for directing robot picking activity in a warehouse environment. In one example of the system/method of the present invention, multiple robots are directed by one or more central processors to move to resource locations based on resource retrieval instructions. Once a robot is at or near a resource location (e.g., by a storage rock with an item on it), the resource may be obtained by the robot and/or placed (e.g., by a picker) on a platform linked to and controlled by the robot. The robot may then be directed to transport the resource to an outbound location (e.g., a loading dock). An assignment algorithm may be applied by the one or more processors to regulate movement of a robot according to a calculated arrival time of the robot at a second location.