Abstract: The present disclosure relates to a method of controlling movement of a cart in response to a change in a travel surface using artificial intelligence and a cart implementing the same, and in a cart robot of one embodiment, an IMU sensor senses a change in a travel surface, and an obstacle sensor senses a distance from an installed object placed in a direction of an advance of the cart robot, to control a moving part of the cart robot.

Abstract: A fitting method includes (a) detecting a first position as a position where fitting of a first object and a second object is determined, (b) moving the first object from the first position toward a determination direction different from a fitting direction and detecting a second position as a position where magnitude of a force applied to the first object reaches a predetermined reference value, and (c) determining that a fitting condition of the first object and the second object is good when a predetermined determination condition including a condition that the second position is within an acceptable position range set according to the first position is satisfied.

Abstract: Systems, methods, and systems are disclosed for a robotic manipulator system including a robotic manipulator, a controller, one or more sensors, and a support structure. The support structure may be non-planar and/or deformable and may be designed to support an object on an upper surface. The one or more sensors may be directed towards the support structure and object. The controller and/or another computing device in communication with the controller may determine geometry of the support structure and may know or determine a compression value of the support structure. Using the compression value and/or geometry of the support structure, the controller may cause the robotic manipulator to grasp the object from the support structure and move the object to a new location.

Abstract: Provided is a process including: obtaining a first set of one or more images generated via an optical gas imaging (OGI) camera and a second set of one or more images generated via a second camera, wherein the first set and the second set correspond to a first location of a plurality of locations in a facility; classifying, via a convolutional neural network (CNN), the first set of one or more images according to whether the one or more images depict a gas leak; and storing a result of classifying the first set in memory.

Abstract: Provided is a control device capable of controlling the operation of a control target according to a detected external force. A control device (200) includes a control unit (210-1) that compares a first external force detected by a force sensor provided in a control target and a second external force estimated on the basis of a torque detected by a torque sensor provided in an a movable portion of the control target, the movable portion enabling the force sensor to be movable, and controls the operation of the control target by correcting a torque command value on the basis of a result of the comparison.

Abstract: Implementations are provided for increasing realism of robot simulation by injecting noise into various aspects of the robot simulation. In various implementations, a three-dimensional (3D) environment may be simulated and may include a simulated robot controlled by an external robot controller. Joint command(s) issued by the robot controller and/or simulated sensor data passed to the robot controller may be intercepted. Noise may be injected into the joint command(s) to generate noisy commands. Additionally or alternatively, noise may be injected into the simulated sensor data to generate noisy sensor data. Joint(s) of the simulated robot may be operated in the simulated 3D environment based on the one or more noisy commands. Additionally or alternatively, the noisy sensor data may be provided to the robot controller to cause the robot controller to generate joint commands to control the simulated robot in the simulated 3D environment.

Abstract: A steering control device includes a control unit configured to control at least an operation of a steering-side motor. The control unit is configured to calculate a target reaction torque; calculate a difference axial force that is used to limit steering for turning the turning wheels in a predetermined direction, the difference axial force being reflected in the target reaction torque; and set a reference angle to one of a steering angle and a turning angle, set a converted angle to an angle obtained by converting another of the steering angle and the turning angle according to a steering angle ratio, and calculate the difference axial force based on a difference between the reference angle and the converted angle.

Abstract: Method and robot arm, where the motor torques of the joint motors of a robot arm are controlled based on a static motor torque indicating the motor torque needed to maintain the robot arm in a static posture, where the static motor torque is adjusted in response to a change in posture of the robot arm caused by an external force different from gravity applied to the robot arm. Further the motor torque of the joint motors is controlled based on an additional motor torque obtained based on a force-torque provided to the robot tool flange, where the force-torque is obtained by a force-torque sensor integrated in the tool flange of the robot arm.

Abstract: A method of programming an industrial robot includes: providing the robot, the robot having a robot arm with an end-effector mounted thereto which is controlled by a robot control unit to manipulate a workpiece which is arranged in a workplace of the robot; associating a target coordinate system with the workplace; taking an image of the workplace and the workpiece by an image capturing device; transmitting the image to a computing device having a human-machine-interface to generate control code for controlling the robot, which is transmitted to the robot control unit; capturing an image of the workplace and the workpiece to be manipulated by the robot; transferring the captured image to the computing device and displaying the captured image on a display associated with the computing device; and displaying the workpiece on the display; marking the workpiece with a marker-object on the display.

Abstract: To provide personalized data for display on a map, a server device obtains location data for a user and identifies locations that are familiar to the user based on the frequency and recency in which the user visits the locations. The server device then provides the familiar locations in search results/suggestions and annotates the familiar locations with a description of a relationship between the familiar location and the user. The server device also includes the familiar locations as landmarks for performing maneuvers in a set of navigation instructions. Furthermore, the server device provides a familiar location as a frame of reference on a map display when a user selects another location nearby the familiar location. Moreover, the server device includes a familiar location as an intermediate destination when the user request navigation directions to a final destination.

Abstract: A control system includes: a controller configured to operate one or more robots in a real space based on an operation program; and circuitry configured to: operate one or more virtual robots based on the operation program in a virtual space, the one or more virtual robots corresponding to the one or more robots respectively; cause the controller to suspend an operation based on the operation program by the one or more robots; simulate a suspended state of the real space after suspension of the operation by the one or more robots, in the virtual space; and resume at least a part of the operation by the one or more virtual robots based on the operation program, in the virtual space in which the suspended state of the real space has been simulated.

Abstract: Techniques described herein include detecting a degree of motion sickness experienced by a user within a vehicle. A suitable combination of physiological data (heart rate, heart rate variability parameters, blood volume pulse, oxygen values, respiration values, galvanic skin response, skin conductance values, and the like), eye gaze data (e.g., images of the user), vehicle motion data (e.g., accelerometer, gyroscope data indicative of vehicle oscillations) may be utilized to identify the degree of motion sickness experienced by the user. One or more autonomous actions may be performed to prevent an escalation in the degree of motion sickness experienced by the user or to ameliorate the degree of motion sickness currently experienced by the user.

Abstract: A mutual recognition method between an unmanned aerial vehicle (UAV) and a wireless terminal, includes: when an image of the UAV is positioned in a predetermined section of an imaging surface of an image sensor in the wireless terminal, receiving, by a server, first state information about the wireless terminal including information about a direction of an external magnetic field of the wireless terminal from the wireless terminal.

Abstract: The subject disclosure relates to features that improve safety for autonomous vehicle (AV) maneuvers and in particular, that improve safety for parallel parking. A process of the disclosed technology includes steps for initiating a parking maneuver, navigating the AV into a parking location, and detecting a roadway grade with respect to a direction of the AV. In some aspects, the process can further include steps for automatically adjusting a wheel angle of the AV based on the roadway grade with respect to the direction of the AV. Systems and machine-readable media are also provided.

Abstract: Techniques are disclosed to perform robotic handling of soft products in non-rigid packaging. In various embodiments, sensor data associated with a workspace is received. An action to be performed in the workspace using one or more robotic elements is determined, the action including moving an end effector of one of the robotic elements relatively quickly to a location in proximity to an item to be grasped; actuating a grasping mechanism of the end effector to grasp the item using an amount of force and structures associated with minimized risk of damage to one or both of the item and its packaging; and using sensor data generated subsequent to the item being grasped to ensure the item has been grasped securely. Control communications are sent to the robotic element via the communication interface to cause robotic element to perform the action.

Abstract: Embodiments of the present disclosure sets forth a computer-implemented method comprising obtaining a starting location and a destination location, determining a plurality of routes from the starting location to the destination location, obtaining affective-cognitive load (ACL) data associated with the plurality of routes, selecting a route included in the plurality of routes based on the ACL data, and transmitting the selected route for output.

Abstract: This disclosure relates generally to navigation of a tele-robot in dynamic environment using in-situ intelligence. Tele-robotics is the area of robotics concerned with the control of robots (tele-robots) in a remote environment from a distance. In reality the remote environment where the tele robot navigates may be dynamic in nature with unpredictable movements, making the navigation extremely challenging. The disclosure proposes an in-situ intelligent navigation of a tele-robot in a dynamic environment. The disclosed in-situ intelligence enables the tele-robot to understand the dynamic environment by identification and estimation of future location of objects based on a generating/training a motion model. Further the disclosed techniques also enable communication between a master and the tele-robot (whenever necessary) based on an application layer communication semantic.

Abstract: Vehicle drive assist systems, methods, and programs display an alert image superimposed on a real view on a display. The systems, methods and programs determine a blind spot area, the blind spot area being an area that becomes a blind spot of a driver of a vehicle due to a front obstacle present on a front side in a traveling direction of the vehicle. The alert image is displayed such that the alert image is superimposed on a target point, the target point being a point where traveling of the vehicle is likely to be influenced when there is a moving obstacle jumping out of the blind spot area.

Abstract: A new controller for use in robots with kinematic loops as well as in most other types of robots (such as those with fully actuated kinematic trees). The controller includes an inverse kinematics (IK) module that implements a versatile IK formulation for retargeting of motions, including expressive motions, onto mechanical systems (i.e., robots with loops and/or without loops). Further, the controller is configured to support the precise control of the position and orientation of end effectors and the center of mass (CoM) (such as of walking robots). The formulation of the algorithms carried out by the IK module safeguards against a disassembly when IK targets are moved outside the workspace of the robot. A regularizer is included in the controller that smoothly circumvents kinematic singularities where velocities go to infinity.

Abstract: A computer-implemented method of determining a location of a mobile device is provided. The method can include receiving inertial data generated at the mobile device, the inertial data including a plurality of samples taken at different times, segmenting the inertial data into pseudo-independent windows, wherein each pseudo-independent window can include a plurality of the samples and wherein one or more initial states for each pseudo-independent window are treated as unknown, estimating a change in navigation state over each pseudo-independent window using the samples of inertial data, and summing the changes in the navigation states over the pseudo-independent windows so as to determine the location of the mobile device.