Abstract: Methods and systems are provided for determining and mitigating vehicle pull force from passing other vehicles. In an exemplary embodiment, methods and systems are provided that include: obtaining sensor data via one or more sensors of a vehicle, the sensor data including both perception sensor data and vehicle dynamics sensor data; identifying, via a processor, one or more additional vehicles to be passed by the vehicle, using the perception sensor data; and predicting and determining, via the processor, a pull force for the vehicle that is caused by the passing of the vehicle by the one or more additional vehicles along with an impact of the pull force on the vehicle, based on both the perception sensor data and the vehicle dynamics sensor data, and control the vehicle to proactively mitigate the pull force on the vehicle; and vehicle with trailer when towing.

Abstract: Generating trajectories from an implicit neural representation (INR) model to predict human mobility in uncertain traffic conditions includes receiving geocoordinate data representing vehicle motion observations of a traffic pattern; receiving a road network based on the geocoordinate data; training the INR model to learn continuous, latent fields of stochastic traffic properties over space and time based on the geocoordinate data; utilizing the INR model to extract spatio-temporal speed distributions from the geocoordinate data; applying a near-shortest-path, heuristic algorithm, weighted by predictions of the INR model, to produce real-world routing choices for traversing the road network; generating trajectories for transportation between an origin and destination in the road network using the algorithm and the predictions of the INR model, wherein the trajectories reflect non-deterministic and diverse route choices in the road network; and outputting generated trajectories to improve routing choices for a

Abstract: The present disclosure provides an Industrial Internet of Things system for monitoring a collaborative robot with dual identification and a control method thereof. The Industrial Internet of Things includes a user platform, a service platform, a management platform and a sensing network platform and an object platform connected in sequence, and the control method comprises: monitoring a target collaborative robot on a production line, obtaining monitoring data, the monitoring data including at least one of image information of the target collaborative robot and displacement sensor data of the target collaborative robot; and processing the monitoring data.

Abstract: Devices, systems, and methods for social behavior of a telepresence robot are disclosed herein. A telepresence robot includes a drive system configured to move the telepresence robot; a control system configured to control the drive system to drive the telepresence robot around a work area; an object detection system configured to determine that a first object encountered by the telepresence robot is a human; and a social path component configured to: determine a first lockout zone having a first radius around the human and a first comfort zone having a second radius around the human, the second radius being larger than the first radius; and instruct the control system to cause the telepresence robot to: avoid traveling through the first lockout zone; move at a first maximum speed within the first comfort zone; and move at a second maximum speed outside of the first comfort zone, wherein the second maximum speed is greater than the first maximum speed.

Abstract: The purpose of the present invention is to eliminate the need, when a robot has been replaced with a new robot that is different in size, for an operator to directly re-input as operation program to make the robot operative. This robot control device comprises: a storage unit that stores an operation program; and a control unit that operates a robot is a robot coordinate system with three orthogonal axes. The control unit is provided with: a mobility range determination unit that determines whether there is, in the operation program, an axis, among the three orthogonal axes, that exceeds a mobility range of the robot; and a correction unit that, if it has been determined by the mobility range determination unit that there is an axis that exceeds the mobility range of the robot, rewrites the operation program so the axis is kept within the mobility range of the robot.

Abstract: A method for classifying a roadway condition on the basis of image data from a camera system includes providing image data which is configured to image at least one portion of the surroundings of the vehicle, at least part of the portion containing the roadway on which the vehicle is driving. The method includes distinguishing diffuse reflection and specular reflection of the roadway by evaluating differences in the appearances of at least one point of the roadway in at least two images. The method also includes determining whether, in at least one image, there are disturbances that have been caused by at least one wheel of a vehicle whirling up a substance covering a roadway as said wheel travels thereover. The method further includes classifying the roadway condition into one of several roadway condition classes, taking account of the results with regard to the reflection type and the disturbance intensity.

Abstract: A system and method for generating simulated vehicles with configured behaviors for analyzing autonomous vehicle motion planners are disclosed. A particular embodiment includes: obtaining configuration instructions and data for each of a plurality of simulated vehicles, a specific driving behavior for each of the plurality of simulated vehicles corresponding to perception data obtained from perception data sensors; and generating a plurality of trajectories and acceleration profiles to transition each of the plurality of simulated vehicles from a current position and speed to a corresponding target position and target speed, the target position and the target speed corresponding to the specific driving behavior for each of the plurality of simulated vehicles.

Abstract: An indoor mobile industrial robot system is configured to provide a weight to a detected object within an operating environment, where the weight relates to how static the feature is. The indoor mobile industrial robot system includes a mechanism configured to translate reflected light energy and positional information into a set of data points representing the detected object having at least one of Cartesian and/or polar coordinates, and an intensity. If any discrete data point within the set of data points representing the detected object has an intensity at or above a defined threshold the entire set of data points is converted into a weight and potentially classified representing a static feature, otherwise such set of data points is classified as representing a dynamic feature having a lower weight.

Abstract: A vehicle information delivery device includes an image processing unit configured to generate vehicle related images indicating the status of a vehicle moving unmanned in a predetermined target area based on camera images taken in the target area where unattended parking is performed, and an information sending unit configured to send delivery information including the vehicle related images to a display terminal visually recognized by a user of the vehicle.

Abstract: A method for optimizing an automated process to select and grip an object by a robot in an arrangement that includes a plurality of robots with regard to a specifiable optimization criterion, wherein the objects to be potentially gripped irregularly occur with respect to their spatial position and a time of their arrival, where detection of objects to be potentially gripped by robots is performed, detection of a priority characteristic as well as an assignment to one of the robots for the objects to be potentially gripped via an automated learning algorithm, taking the optimization criterion into account, and where selection and gripping depending on the assignment and the priority characteristic is implemented.

Abstract: A belt conveyor calibration method includes transporting a marker by a belt of a belt conveyor, imaging the marker by a first camera, detecting the marker passing through one section of a plurality of sections formed by division of a first imaging area of the first camera from a captured image of the first camera, moving a second camera by a robot and tracking and imaging the detected marker by the second camera, and calculating and storing a correction value as a difference between a position of the marker estimated from a transportation amount of the belt and a position of the marker detected from an image of the marker tracked and imaged.

Abstract: The present disclosure relates to a control device, a control method, and a program capable of supporting an object with a more appropriate supporting force. The control device includes a supporting force control unit that controls a supporting force for supporting an object on the basis of information regarding a shape of a contact portion in contact with the object and information regarding a shear force of the contact portion. The information regarding the shear force includes, for example, information regarding a shear displacement of the contact portion. The present disclosure can be applied to, for example, a control device, a control method, an electronic device, a robot, a support system, a gripping system, a program, and the like.

Abstract: An occupancy verification including one or more processors, configured to receive occupancy grid data representing a plurality of cells of an occupancy grid and for each cell of the plurality of cells, a probability of whether the cell is occupied; receive object location data, representing one or more locations of one or more objects identified using a model; map the object location data to one or more cells of the plurality of cells based on the one or more locations of the one or more objects; determine comparison grid data, representing the plurality of cells of the occupancy grid and for each cell of the plurality of cells, a probability of whether the cell is occupied based on whether the object location data are mapped to the cell; and compare the occupancy grid data to the comparison grid data using at least one comparing rule.

Abstract: A deburring device includes a robot program creating unit that creates a program from data of an object, a deburring part detecting unit that detects a position for a deburring part on the object, and a robot program updating unit that updates the program by the detected position of the deburring part. The deburring device also includes a force control unit that controls to yield a predetermined pressing force, an actual path acquiring unit that acquires an actual path of a robot when controlled at the predetermined pressing force by the updated program, and a path correction parameter calculating unit that calculates a correction parameter for the position for the deburring part on the object from the path of the robot from the visual sensor and the actual path.

Abstract: Four-wheel steering of a vehicle, e.g., in which leading wheels and trailing wheels are steered independently of each other, can provide improved maneuverability and stability. A first vehicle model may be used to determine trajectories for execution by a vehicle equipped with four-wheel steering. A second vehicle model may be used to control the vehicle relative to the determined trajectories. For instance, the second vehicle model can determine leading wheels steering angles for steering leading wheels of the vehicle and trailing wheels steering angles for steering trailing wheels of the vehicle, independently of the leading wheels.

Abstract: Systems and method for controlling the attitude maneuvers of a spacecraft in space are provided. The method automatically generates optimal trajectories in real-time to guide a spacecraft, providing a much more robust and efficient method than predefined trajectories, to model errors or disturbances. These methods do not rely in predefined trajectories and their associated feed-forward term. The systems comprise sensors, attitude control mechanisms, and a control module to orient the spacecraft in real-time, such that the spacecraft reaches a desired target attitude following an optimal path in the state space and is locally and asymptotically stable.

Abstract: A method includes, by a processor, acquiring number of persons information that indicates a number of users, including users who ride in vehicles, who depart from a facility at each of a predetermined time period, weather information for each predetermined time period, and vehicle information relating to vehicles traveling in a periphery of the facility, determining traffic jam status that indicates absence/presence of a traffic jam on a road located in a vicinity of the facility in the predetermined time period, by using the vehicle information; and generating a learned model for predicting a traffic jam of a road by machine learning using, as teaching data, the number of persons information, the weather information, and the traffic jam status that is associated with the number of persons information and the weather information.

Abstract: Implementations set forth herein relate to generating training data, such that each instance of training data includes a corresponding instance of vision data and drivability label(s) for the instance of vision data. A drivability label can be determined using first vision data from a first vision component that is connected to the robot. The drivability label(s) can be generated by processing the first vision data using geometric and/or heuristic methods. Second vision data can be generated using a second vision component of the robot, such as a camera that is connected to the robot. The drivability labels can be correlated to the second vision data and thereafter used to train one or more machine learning models. The trained models can be shared with a robot(s) in furtherance of enabling the robot(s) to determine drivability of areas captured in vision data, which is being collected in real-time using one or more vision components.

Abstract: The present invention relates to, for example, a vehicle control device including a driving force control unit that controls a driving force generated by a wheel of a vehicle; and a braking force control unit that controls a braking force generated by the wheel; where the driving force control unit generates the driving force of a first prescribed amount and the braking force control unit generates the braking force of a second prescribed amount to control the speed of the vehicle to be constant; and acceleration or deceleration are both controllable by performing one of control of the driving force by the driving force control unit and control of the braking force by the braking force control unit.

Abstract: An article transfer facility (100) includes a transfer device (3) that performs a first operation to take out an article (W) that are supported by a first container (C1), from the first container (C1), and a second operation to load the article (W) taken out from the first container (C1), onto a second container (C2); and an inclination device (5) that supports the second container (C2) at a predetermined position (P2), wherein the second container (C2) has a rectangular mounting surface (S) onto which the articles (W) are to be mounted, and is formed in a box shape with an open upper surface, and the inclination device (5) supports the second container (C2) in an inclined state such that a target corner portion (Sct) that is one of a plurality of corner portions (Sc) of the mounting surface (S) is located lower than the other corner portions (Sc).