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.

The present disclosure discloses a mobile robot positioning method and system based on wireless ranging sensors, and a chip. The mobile robot positioning method adopts a manner of controlling a mobile robot to traverse two target positions successively to acquire a distance between the mobile robot at each traversed position and a fixed positioning base station, rather than calculate distances between the robot at the same position and different base stations, such that the trouble of arranging a plurality of base stations in a positioning area is reduced.

A method for determining a motion path on a surface in an environment, along which motion path a mobile appliance, in particular a robot, preferably a domestic robot or a robot vacuum cleaner, is intended to move. The method includes obtaining environment information and determining a region of the surface intended to be covered by the motion of the mobile appliance; determining, while taking into account the environment information, whether within the region there is at least one uneven area in the surface that can be negotiated by the mobile appliance; and determining the motion path while taking into account the at least one uneven area, if there is one. A mobile appliance is also described.

A GPS directed vehicle for cleaning airport runway surfaces. The vehicle uses an ultra-high pressure washer for cleaning rubber off the surfaces of the runway, and a vacuum system for the collection of debris. A GPS device allows an operator to track a cleaning line so as to allow no more than 25 mm overlap of surfaces to be cleaned. An iPad can be used to highlight Google maps for calculating a runway area to be treated. Recording allows the exact location of last treated surface area to allow exact location of an untreated surface area.

A portable robotic platform system and method for automatically detecting, locating, and marking underground assets are provided. The portable robotic platform includes a housing with a sensor module including ground penetrating radar (GPR), LiDAR, and electromagnetic (EM) sensors. The robotic platform automatically collects GPR and EM data and uses onboard post-processing techniques to interpret the sensor data and identify the location(s) of underground infrastructure. The portable robotic platform can be deployed to apply paint to a ground surface to identify the located underground assets.

An autonomous driving robot includes a driving unit that moves the autonomous robot; a camera; a traveling distance measurement sensor; and a control unit that estimates a location of the autonomous robot using a captured image and traveling distance information. In this case, the operation control program generates a robot viewpoint map based on the image captured by the camera, estimates a location of the autonomous robot based on the robot viewpoint map and the measured traveling distance information, and generates a global map based on the robot viewpoint map and position estimation information, and the operation control program inputs the generated robot viewpoint map and global map into a style-transfer model, and inputs a style-transferred robot viewpoint map and a style-transferred global map output by the style-transfer model into the operation agent to correct the estimated position.

Systems and methods are described for reacting to a feature in an environment of a robot based on a classification of the feature. A system can detect the feature in the environment using a first sensor on the robot. For example, the system can detect the feature using a feature detection system based on sensor data from a camera. The system can detect a mover in the environment using a second sensor on the robot. For example, the system can detect the mover using a mover detection system based on sensor data from a lidar sensor. The system can fuse the data from detecting the feature and detecting the mover to produce fused data. The system can classify the feature based on the fused data and react to the feature based on classifying the feature.

Provided is a highly reliable, cost-effective scattered object collection system that can efficiently collect scattered objects by reducing unnecessary traveling of a traveling collector. The scattered object collection system includes a traveling collector that performs a collecting operation by picking up balls B while traveling in a work area W, sets a virtual work area Z (or a virtual priority work area Za) to an area in the work area W where balls are relatively densely present and in the vicinity of the storage space of balls, and allows the traveling collector to perform a collecting operation in the virtual work area Z (or the virtual priority work area Za) with higher priority than the other areas.

A system to remotely operate a vehicle in the presence of limited bandwidth and high latency is disclosed. A remote driver station calculates and transmits a trajectory to a vehicle. The vehicle relocalizes and then follows said trajectory. Images captured by cameras on the vehicle are processed and then compressed for transmission over the limited bandwidth connection to the remote driver. Other sensors on the vehicle collect information which is transmitted to the remote driver as well as aiding in the processing and compression of visual information.

Systems and methods for robotic control using LiDAR assisted dead reckoning are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot may accurately localize itself over time by detecting parallelized environmental surfaces, such as walls or shelves arranged in a parallel manner, extracting a primary orientation of those surfaces using LiDAR data, and utilizing the primary orientation to accurately define its heading angle in real time, thereby enabling localization via dead reckoning.