Abstract: A robot system includes a robot including a plurality of fingers for holding a target object and a control device configured to control a motion of the robot. The control device includes one or more processors. The processors acquire an image of a first target object and a second target object taken by an imaging device. The processors control the motion of the robot based on the image such that the robot moves the first target object with at least one finger included in the fingers in a direction in which a gap is formed between the first target object and the second target object, inserts at least one finger included in the fingers into the gap, and holds the first target object.

Abstract: An overshoot amount detection method includes a synchronization step of synchronizing a signal of an inertial sensor with a signal of an encoder based on a first synchronizing signal output from the inertial sensor during a signal synchronizing operation and a second synchronizing signal output from the encoder during the signal synchronizing operation, a signal generation step of generating a first signal by twice integration of a first detection signal output from the inertial sensor during a working operation and removal of a low-frequency component contained in the first detection signal and generating a second signal for supplement of the low-frequency component of the first signal from a second detection signal output from the encoder during the working operation, and an overshoot amount detection step of detecting an overshoot amount of an arm based on the first signal and the second signal.

Abstract: Embodiments of the present invention include a collaborative manufacturing system utilizing a plurality of mobile agents. The mobile agents operate dual robotic arms to improve single and multi-material builds' efficiency. In some embodiments, the dual robotic arms work together in the same area to create multi-functional components. In addition, the mobile agents can change tool heads on the arms to allow for hybrid manufacturing such as pick and place, additive, and subtractive manufacturing. One or more mobile agents interact with other mobile agents, thereby increasing the end product's efficiency and quality. Mobile agents utilize swarm manufacturing techniques to improve the manufactured product's time efficiency further and use machine learning to adjust and re-assign mobile agents constantly.

Abstract: A robot obtains image data representative of an environment comprising a first region and a second region. A microphone receives sound from the environment. The robot determines, using the image data and audio data derived based on the received sound, whether the sound is received from the first region, and outputs a control signal for controlling the robot based on the audio data. Sounds received from the first region are processed as voice commands on the basis that one of the first region and the second region comprises a predetermined type of inanimate object. Sounds received from the second region are processed in a different manner.

Abstract: The present disclosure is related to methods and systems for controlling a snake-arm robot. The method includes receiving real-time image data associated with an operating environment or a location of a workpiece from optical sensor(s) mounted on a robot head of the robot; receiving input data describing a desired pose of the robot head; computing and translating a desired displacement of the robot head; computing a position of each of the links of the snake-arm robot to follow motion of the robot head, a current position of each the links, and data required to move joints connecting the links to move the robot to the desired pose; generating movement instructions; and transmitting the movement instructions to a drive motor associated with an introduction device or controllers associated with servo-motors operably connected to joints connecting the links of the snake-arm causing the robot head to move to the desired pose.

Abstract: The present invention relates to a robot and method for estimating an orientation on the basis of a vanishing point in a low-luminance image, and the robot for estimating an orientation on the basis of a vanishing point in a low-luminance image according to an embodiment of the present invention includes a camera unit configured to capture an image of at least one of a forward area and an upward area of the robot and an image processor configured to extract line segments from a first image captured by the camera unit by applying histogram equalization and a rolling guidance filter to the first image, calculate a vanishing point on the basis of the line segments, and estimate a global angle of the robot corresponding to the vanishing point.

Abstract: In an example embodiment, a novel “process assembly line” solution is provided that organizes software robots in a manner that, once configured, allows them to be duplicated and cloned into multiple scenarios, including in organizational structures where one software robot is triggered or called by another software robot. Instead of designing software robots with multiple functionalities in each to perform complex situations, the process assembly line can utilize software robots with single functions. This aids developers in building robust software robots and reduces potential errors.

Abstract: A method of operating a mobile robot includes displaying, on a display unit, a photographing menu including a first photographing item for allowing the mobile robot to perform a specific motion for photographing and a second photographing item for allowing the mobile robot to photograph a user, displaying a screen for guiding a motion setting of the mobile robot on the display unit when the first photographing item is selected, performing, by the mobile robot, a corresponding motion based on an input motion setting for a first reference time when the motion setting of the mobile robot is input, and displaying a result screen on the display unit after the first reference time has elapsed.

Abstract: A diagnostic system includes an acquirer configured to acquire current waveform data representing a waveform relating to a current supplied to a driving device of an apparatus and a determiner configured to determine a degree of abnormality in the apparatus from a varying portion of the waveform, the varying portion corresponding to a varying time period during which a rotation speed of the driving device increases or decreases.

Abstract: A method for controlling an apparatus for a first vehicle includes: receiving first positional information including a current position of the first vehicle, a traveling direction of the first vehicle, and a traveling speed of the first vehicle; receiving second positional information including a current position of a second vehicle, a traveling direction of the second vehicle, and a traveling speed of the second vehicle; estimating a future position of the first vehicle on the basis of the first positional information; estimating a future position of the second vehicle on the basis of the second positional information; determining whether a distance between the future position of the first vehicle and the future position of the second vehicle is shorter than a threshold value, and notifying a driver of the first vehicle of a result of the determination when the distance is shorter than the threshold value.

Abstract: A mobile robot is configured for operation in a commercial or industrial setting, such as an office building or retail store. The robot can patrol one or more routes within a building, and can detect violations of security policies by objects, building infrastructure and security systems, or individuals. In response to the detected violations, the robot can perform one or more security operations. The robot can include a removable fabric panel, enabling sensors within the robot body to capture signals that propagate through the fabric. In addition, the robot can scan RFID tags of objects within an area, for instance coupled to store inventory. Likewise, the robot can generate or update one or more semantic maps for use by the robot in navigating an area and for measuring compliance with security policies.

Abstract: A computing system and method for object recognition is presented. The method includes the computing system obtaining an image for representing the one or more objects, and generating a target image portion associated with one of the one or more objects. The computing system determines whether to classify the target image portion as textured or textureless, and selects a template storage space from among a first and second template storage space, wherein the first template storage space is cleared more often relative to the second template storage space. The first template storage space is selected in response to a textureless classification, and the second template storage space is selected as the template storage space in response to a textured classification. The computing system performs object recognition based on the target image portion and the selected template storage space.

Abstract: A design method of serial manipulator that comprises an end effector, a number of random-access links, and a number of motors, includes: obtaining a desired motion profile of the end effector; discretizing the desired motion profile into a plurality of points, wherein each of the points carries information of speed, acceleration, and force/torque of the end effector at the point; determining the number of degrees of freedom of the serial manipulator, and initializing the length of each of the links and the motor type of each of the motors; and at each of the points, optimizing the initialized lengths of the links and the motor types of the motors by calculating a dynamic manipulability ellipsoid at the end effector, to obtain desired lengths of the links and desired motor types of the motors, which allows the end effector to execute the desired motion profile under predetermined constraints.

Abstract: A robot including a manipulator includes: an image-pickup acquisition unit configured to acquire an image of an environmental space including a target object to be grasped; and a control unit configured to control a motion performed by the robot, in which the control unit causes the robot to acquire, by the image-pickup acquisition unit, a plurality of information pieces of the target object to be grasped while it moves the robot so that the robot approaches the target object to be grasped, calculates, for each of the information pieces, a grasping position of the target object to be grasped and an index of certainty of the grasping position by using a learned model, and attempts to grasp, by moving the manipulator, the target object to be grasped at a grasping position selected based on a result of the calculation.

Abstract: A robotic platform for a tapping machine includes a sensor, a controller, a wireless interface directly or indirectly connected to the controller, a frame for receiving a tapping machine and a motor attached to the frame for moving the frame with the tapping machine received thereon. The frame is configured to exhibit dimensions and strength to hold a tapping machine, or other machine with a proportional-derivative control, where upon commands provided to it by the controller, the motor moves the frame and tapping machine, or other machine, through the four positions required by the ASTM test methods, under wireless control.

Abstract: A control method includes: (a) setting a first operation mode using a first deviation threshold as a threshold to detect a deviation error in an amount of control and a second operation mode using a second deviation threshold that is higher than the first deviation threshold; and (b) selecting one of the first operation mode and the second operation mode and executing an operation of a robot.

Abstract: A method is provided that includes controlling a robotic gripping device to cause a plurality of digits of the robotic gripping device to move towards each other in an attempt to grasp an object. The method also includes receiving, from at least one non-contact sensor on the robotic gripping device, first sensor data indicative of a region between the plurality of digits of the robotic gripping device. The method further includes receiving, from the at least one non-contact sensor on the robotic gripping device, second sensor data indicative of the region between the plurality of digits of the robotic gripping device, where the second sensor data is based on a different sensing modality than the first sensor data. The method additionally includes determining, using an object-in-hand classifier that takes as input the first sensor data and the second sensor data, a result of the attempt to grasp the object.

Abstract: The present disclosure generally relates to the field of robotics and computer animation, more particularly, method and apparatus to solve the inverse kinematics problem to control a kinematic chain such as a robot arm or an animation character's skeleton to reach a target position. The new method simulates a kinematic chain whose links and joints are elastic and can be distorted. The method distorts the kinematic chain to move its end to the target position, calculates distortions, and iteratively adjusts link and joint configurations of the kinematic chain to reduce distortions while keeping its end at the target position until a solution with near zero distortions is found. The resulting link and joint configurations of the simulated kinematic chain then can be used for the actual kinematic chain to reach the same target position.

Abstract: Methods, systems, and apparatus, for an autonomous vehicle navigation maintenance system. In one aspect, an autonomous vehicle monitoring system includes a mounting surface located on an autonomous vehicle, and a thermal imaging system affixed to the mounting surface, the thermal imaging system including a thermal imaging camera, a replaceable filter, and a filter fixture configured to affix the replaceable filter to the thermal imaging camera and aligned with an optical axis of the thermal imaging camera, and where maintenance of the replaceable filter does not include re-calibrating the thermal imaging camera.

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.