Abstract: An embodiment rehabilitation robot control apparatus includes a brainwave signal measuring device configured to measure a brainwave signal of a user, a preprocessing device configured to preprocess the measured brainwave signal, a classification device configured to classify a motor intention of the user based on the brainwave signal preprocessed by the preprocessing device, and a controller configured to reflect the motor intention of the user in real time to control an operation or a stop of a rehabilitation robot.

Abstract: Provided is a method for controlling a robot including a base, a robot arm coupled to the base, and a drive unit including a motor for driving the robot arm. The method includes a first step of acquiring weight information including information on a weight of an end effector installed on the robot arm and a weight of an object to be worked by the end effector; a second step of determining a frequency component to be removed from a drive signal for driving the motor based on the weight information acquired in the first step; and a third step of removing the frequency component determined in the second step from the drive signal to generate a correction drive signal.

Abstract: Provided herein is a method for controlling a manipulator, comprising accepting an initial pose of a load and a task for moving the load and retrieving using a mapping function, an identification trajectory corresponding to the initial pose of the load and controlling a plurality of actuators of the manipulator to move the load according to the retrieved identification trajectory and obtaining measured motion data and estimated motion data of the load each corresponding to motion of the load. The method further comprises estimating parameters of the load based on the measured motion data and the estimated motion data, obtaining a model of the manipulator having the load with the estimated parameters, and determining a performance trajectory to move the load according to the task based on the obtained model of the manipulator. The method further comprises controlling the actuators to move the load according to the performance trajectory.

Abstract: A method for estimating a pose of a humanoid robot includes: processing obtained pose parameters of a waist of the humanoid robot and plantar motion parameters of the humanoid robot to obtain the measured pose parameters of a center point of the waist of the humanoid robot; calculating predicted pose parameters of the center point of the waist according to the obtained pose parameters of the waist; and fusing the measured pose parameters and the predicted pose parameters to obtain estimated pose parameters of the center point of the waist.

Abstract: Devices, systems, and methods for time calibration. The method comprises determining a first reference position of a robot in a robot coordinate system based on first feedback information received from the robot; determining an association between the first reference position and first sensing information receive from a sensor; receiving, from the robot, second feedback information associated with a second motion of the robot and, from the sensor, second sensing information associated with the second motion; and determining a time delay between a sensing time point when a sensing position of the robot in the second motion is sensed by the sensor and a recording time point when the sensing position is recorded by the robot in the second motion.

Abstract: Systems, methods, and computer program products for generating training data are described. Action data and context data are recorded for a robot body performing an action or task in an environment. The context data is augmented virtually to include variations from the recorded environment while the action data remains unchanged, and instances of training data are generated including the augmentations, to produce a large and varied training data set.

Abstract: Techniques are discussed for predicting an occupancy of visible region of an environment. For instance, a vehicle may generate sensor data representing an environment. The vehicle may then analyze the sensor data to determine an occluded region of the environment a visible region of the environment. Additionally, the vehicle may determine at least one prediction probability associated with occupancy of the visible region over a future period of time. In some instances, the vehicle determines the at least one prediction probability by inputting data representing at least the occluded region and the visible region into a machine learned model and receiving the at least one prediction probability from the machine learned model. Using the at least one prediction probability, the vehicle may then determine and perform one or more actions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that distributes skill bundles that can guide robot execution. One of the methods includes receiving data for a skill bundle from a skill developer. The data can include a definition of one or more preconditions for a robotic system to execute a skill; one or more effects to an operating environment after the robotic system has executed the skill; and a software module implementing the skill. The software module can define a state machine of subtasks. A skill bundle can be generated from the data received from the skill developer. Data identifying the generated skill bundle can be added to a skill registry. The skill bundle can be provided to the execution robot system for installation on the robot execution system.

Abstract: According to the present invention, a moving body capable of moving within a preset range of movement acquires an image from the environment surrounding the location of the moving body, and determines entry determination conditions for obtaining a result of an entry determination as to whether or not the moving body is allowed to enter a region identified by the location of the moving body and the image. A management terminal outputs the entry determination conditions and the image to an output device, and receives modification information relating to the entry determination conditions from an input device. A server uses the modification information received by the input device of the management terminal to perform learning, including updating of the entry determination conditions, thereby setting the movement range of the moving body, the movement of which is controlled in accordance with the entry determination result.

Abstract: A computer-implemented method for controlling a robot, the method comprising: determining a first value for a first joint parameter associated with a first continuum joint included in the robot and a first value for a second joint parameter associated with the first continuum joint, wherein the first joint parameter indicates a bending radius of a flexible portion of the continuum joint, and the second joint parameter indicates a rotation of the flexible portion of the continuum joint with respect to a base portion of the first continuum joint; and positioning an end portion of the robot at a final target location based on the first value of the first joint parameter and the first value of the second joint parameter.

Abstract: The present invention relates to methods for learning a robot task and robots systems using the same. A robot system may include a robot configured to perform a task, and detect force information related to the task, a haptic controller configured to be manipulatable for teaching the robot, the haptic controller configured to output a haptic feedback based on the force information while teaching of the task to the robot is performed, a sensor configured to sense first information related to a task environment of the robot and second information related to a driving state of the robot, while the teaching is performed by the haptic controller for outputting the haptic feedback, and a computer configured to learn a motion of the robot related to the task, by using the first information and the second information, such that the robot autonomously performs the task.

Abstract: The present invention relates to a robot and a control method therefor and, more particularly, to a robot and a control method therefor, the robot detecting peripheral obstacles and structures by using an image in front of same, thereby providing an efficient and safe moving path. A robot control method according to one embodiment of the present invention comprises the steps of: capturing an image; acquiring a first image of which the bottom surface is separated in the image; recognizing obstacles included in the image by using a learned first artificial intelligence model; allowing a robot to acquire and store a second image in order to perform a task on the basis of the information about the first image and the region including the recognized obstacles; and allowing the robot to move on the basis of the second image.

Abstract: An apparatus for automated collision avoidance includes a sensor configured to detect an object of interest, predicting a representation of the object of interest at a future point in time, calculating an indication of a possibility of a collision with the object of interest based on the representation of the object of interest at the future point in time, and executing a collision avoidance action based on the indication.

Abstract: A robot control device includes: a learned model created through learning work data composed of input and output data, the input data including states of a robot and the surroundings where humans operate the robot to perform a series of works, the output data including human operation corresponding to the case or movement of the robot caused thereby; a control data acquisition section that acquires control data by obtaining output data related to human operation or movement from the model, being presumed in response to and in accordance with the input data; a completion rate acquisition section acquiring a completion rate indicating to which progress level in the series of works the output data corresponds; and a certainty factor acquisition section that acquires a certainty factor indicating a probability of the presumption in a case where the model outputs the output data in response to the input data.

Abstract: A control device includes a motion controller configured to control operation of a mechanical apparatus according to an operational command, a correction controller configured to correct the operation of the mechanical apparatus according to manipulational information outputted from a manipulating device, a memory part configured to store first operational information indicative of the operation of the mechanical apparatus, and correctional information indicative of the correction made by the correction controller, and a learning part configured to carry out machine learning using the first operational information and the correctional information corresponding to the first operational information. The motion controller controls the operation of the mechanical apparatus according to the operational command based on the command of the learning part, and the manipulating device outputs the manipulational information based on second operational information indicative of motion of the manipulating device.

Abstract: The present application provides a kinematics modeling method, apparatus and device for a multi-degree-of-freedom mechanism and a storage medium. The method includes: constructing a point coordinate system, and constructing the transformation matrix; constructing transformation matrices of two rotating axes and the transformation matrix; constructing the forward kinematics model based on the transformation matrices of the point coordinate system, the two rotating axes and the workpiece coordinate system; solving the motor value of the rotating axis through the rotation matrix of the end-effector, using the translation matrix of the end-effector as a non-homogeneous linear equation set, solving the motor value of linear axis.

Abstract: The motion detecting device that detects motion of an operator's finger for remotely operating a multi-articulated robot includes a device main body that is installed such that the finger is placed thereon, a contact part that follows a shape of the finger in the device main body and is in contact with the finger, and a detection part that detects the motion of the finger on the basis of a pressing state of the finger against the contact part.

Abstract: A robotic singulation system is disclosed. In various embodiments, sensor data image data associated with a plurality of items present in a workspace is received. The sensor data is used to determine and implement a plan to autonomously operate a robotic structure to pick one or more items from the workspace and place each item singly in a corresponding location in a singulation conveyance structure. The plan includes performing an active measure to change or adapt to a detected state or condition associated with one or more items in the workspace.

Abstract: An advertising method for a shuttle comprises by a controller, responsive to identifying a drop-off location and a business paying to influence a route traveled by the shuttle, selecting one of a plurality of routes to the drop-off location according to a priming estimate indicating that points of interest along the one share more characteristics with the business relative to others of the plurality; and commanding the shuttle to travel the one.

Abstract: A remote robot system and a method of controlling a remote robot system capable of responding appropriately according to a user are provided. A remote robot system includes: a robot configured to perform a predetermined operation including collection of local information near the robot; a guide terminal capable of remotely operating the operation of the robot; and a participant terminal capable of remotely communicating with the guide terminal, in which the participant terminal includes: a display panel configured to output the local information acquired from the robot to the user; and an interest detection unit configured to detect user's interest in the output local information.