There is provided a mobile body that includes an imaging unit to capture an image of an environment around the mobile body, an estimation unit to estimate a position of the mobile body on the basis of the image captured by the imaging unit, a calculation unit 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 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 technique for detection of an obstacle by a UAV includes arriving above a location at a first altitude by the UAV; navigating a descent flight pattern from the first altitude towards the location; acquiring aerial images of the location below the UAV with a camera system disposed onboard the UAV; and analyzing the aerial images with a machine vision system disposed onboard the UAV that is adapted to detect a presence of the obstacle in the aerial images. The descent flight pattern is selected to increase perception by the machine vision system of the obstacle.

Systems and methods provide for estimating a trajectory of a robot by fusing a plurality of robot velocity measurements from a plurality of robot sensors located within a robot to generate a fused robot velocity based on the accuracy of those robot velocity measurements and applying Kalman filtering to the fused robot velocity to compute a current robot location.

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 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.

A system and method for constructing a collaborative digital twin scene model for multiple underground robots belongs to the technical field of digital twin modeling for mines. The system includes a master robot i and sub-robots, both of which are connected to a main control module. The master robot i is equipped with a visualization module, a perception module, a computation module, and a communication module. The system and method for constructing a collaborative digital twin scene model for multiple underground robots is adopted to accurately measure and model the geometric and physical structures of tunnels. It enables the construction of a colored mesh map, which is further imported into Unity3D. Through this process, the pose transmission of the master robot i and the sub-robots within the UWB ranging range is realized, and the local colored mesh maps are stitched into a global colored mesh map.

A navigation method applicable to a robot includes: (a) setting a first position coordinate and first movement information; (b) measuring a plurality of to-be-sensed distances in different directions by using a plurality of distance sensors; (c) inputting the plurality of sensed distances, the first position coordinate, and the first movement information into a neural network model to obtain second movement information; (d) setting the second movement information as the first movement information for a next round of a decision-making process; (e) driving, based on the second movement information, the robot to move from the first position coordinate to a second position coordinate; (f) setting the second position coordinate as the first position coordinate for a next round of the decision-making process; and (g) repeating steps (b) to (f) until a distance between the second position coordinate and a destination coordinate is less than a threshold.

A robot configured for inspection of a pipe is disclosed herein. The robot can include a housing, a sensing device coupled to the housing, a carbon-neutral power source positioned within the housing, a plurality of wheels rotatably coupled to the housing, and a computing device communicably coupled to the sensing device and the carbon-neutral power source. The computing device can include a processing unit and a memory to store a software stack that, when executed by the processing unit, causes the computing device to: receive a signal from the sensing device, detect a condition of the pipe based on the received signal, generate a situational alert based on the detected condition, and transmit the situational alert to a user of the robot.

A method of and system for navigation and manipulation for a robot can include obtaining, by at least one camera and at least one depth sensor, a first visual data set and translating the first visual data set into a continuous three-dimensional map. The three-dimensional map can include semantic information and geometric information. The method and system may further include receiving instruction data and converting the instruction data into at least one task for the robot within the continuous three-dimensional map.