Abstract: An example method includes determining objects and actions associated with the objects for completing a task to be executed by a robotic system, where each action is associated with trajectory. The method further includes determining a pose for each person in an environment associated with the robotic system, predicting a trajectory for each person based on the determined pose associated with the respective person and the actions and trajectories associated with the actions, and adjusting trajectories for one or more of the actions to be performed by the robotic system based on the predicted trajectories for each person.

Abstract: A method and a system for automatically securing the operation of a robot system and corresponding components of the system, wherein operation is controlled by a mobile operating device. The robot system receives presence signals transmitted from a mobile operating device via a short-range first signal connection and an operating signal transmitted via a second signal connection designed to be independent of the first signal connection. The operating signal contains a safety-relevant control command for the robot system. The control command is released for execution by the robot system only if a presence check has ascertained that the last received presence signal satisfies a presence criterion specified with respect to the determination of a spatial proximity of the operating device to the robot system. A configuration signal derived from the result of the presence check is transmitted back to the operating device for configuration based on the result.

Abstract: A system for trajectories imitation for robotic manipulators is provided. The system includes an interface configured to receive a plurality of task descriptions, wherein the interface is configured to communicate with a real-world robot, a memory to store computer-executable programs including a robot simulator, a training module and a transfer module, and a processor, in connection with the memory. The processor is configured to perform training using the training module, for the task descriptions on the robot simulator, to produce a plurality of source policy with subgoals for the task descriptions. The processor performs training using the training module, for the task descriptions on the real-world robot, to produce a plurality of target policy with subgoals for the task descriptions, and update the parameters of the transfer module from corresponding trajectories with the subgoals for the robot simulator and real-world robot.

Abstract: The present invention relates to a near-site robotic construction system. The system includes a work station situated on a near-site position in a close proximity to a building foundation on which a building is under construction and providing shelter and workspace for at least one robot to work; and a computer-assisted cloud based near-site robotic construction platform installed on a cloud server system and configured to provide for a user to operate through a web browser, import and extract a building information modelling data, and plan a predetermined motion command set partly based on the extracted building information modelling data, wherein the at least one robot is configured to work in accordance with the predetermined motion command set to prefabricate a plurality of components for the building in the work station on the near-site position.

Abstract: A humanoid robot control method, a mobile machine using the same, and a computer readable storage medium are provided. The method includes: mapping posture information of leg joints of a human body to leg joint servos of a humanoid robot to obtain an expected rotation angle and an expected rotation angular velocity of non-target optimized joint servos of the leg joint servos and an expected rotation angle and an expected rotation angular velocity of target optimized joint servos of the leg joint servos; obtaining an optimization objective function corresponding to the target optimized joint servos of the leg joint servos; optimizing the expected rotation angle and the expected rotation angular velocity of the target optimized joint servos to obtain a corrected expected rotation angle and a corrected expected rotation angular velocity of the target optimized joint servos; and controlling each of the leg joint servos of the humanoid robot.

Abstract: A method for detecting a ground attribute of a legged robot includes obtaining a collision audio of a foot of the legged robot with a ground; and detecting a workable level attribute of the ground in a working environment of the legged robot according to the collision audio. The sound of the collision between the foot of the robot and the ground is collected, and the workable level attribute of the ground in the working environment of the legged robot is detected based on the sound, so that the operable level attribute can be effectively used to control the legs of the legged robot. On the one hand, the motion noise of the legged robot can be reduced, and on the other hand, the power consumption of the legged robot can be reduced, thereby increasing its range of motion.

Abstract: A method for interconnecting a first robot with at least one second robot, each robot including at least: a first program, a second program, a third program, the method including the following steps, implemented by the second program after reception of a first message from the third program: conversion of the first message into a second message, the second message being formatted according to a predefined object structure including a field typ_msg indicating a type of the message amongst the types: command, query, or information; transmission of the second message to at least one program amongst: a first program belonging to the same robot, a second program of another robot.

Abstract: An automation server accesses a task for a robotic device. The automation server generates motor control commands for the robotic device to complete the task. The automation server transmits, via a network and in a format defined by an Application Program Interface (API), the motor control commands from the automation server to a fleet manager associated with the robotic device, the motor control commands for forwarding from the fleet manager to the robotic device. The automation server receives, from one or more sensors attached to the robotic device and via the network, robotic device sensor data. The automation server receives, from multiple remote sensors and via the network, remote sensor data. The automation server adjusts the generated motor control commands to complete the task based on the robotic device sensor data and the remote sensor data.

Abstract: A robot interference checking motion planning technique using point sets. The technique uses CAD models of robot arms and obstacles and converts the CAD models to 3D point sets. The 3D point set coordinates are updated at each time step based on robot and obstacle motion. The 3D points are then converted to 3D grid space indices indicating space occupied by any point on any part. The 3D grid space indices are converted to 1D indices and the 1D indices are stored as sets per object and per time step. Interference checking is performed by computing an intersection of the 1D index sets for a given time step. Swept volumes are created by computing a union of the 1D index sets across multiple time steps. The 1D indices are converted back to 3D coordinates to define the 3D shapes of the swept volumes and the 3D locations of any interferences.

Abstract: A total centroid state estimation method as well as a humanoid robot and a computer readable storage medium using the same are provided. The method includes: obtaining a motion state of each real joint of the humanoid robot and a motion state of its floating base, where the floating base is equivalent to a plurality of sequent-connected virtual joints; calculating a joint position, a centroid position, and a rotation matrix of each link in the world coordinate system in sequence using the chain rule of homogeneous multiplication according to the position of the joint corresponding to the link to solve a Jacobian matrix of the centroid of the link; solving a total centroid Jacobian matrix based on the Jacobian matrix of the centroid of each link and the total mass; and calculating the total centroid velocity based on the total centroid Jacobian matrix and other parameters.

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: 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: In one embodiment, a method includes accessing a trajectory plan for a task to be executed by a robotic system, determining actions to constrain the trajectory plan based on information associated with an environment associated with the robotic system, wherein pose-based waypoints and joint positions of the robotic system would be constrained by the actions, determining joint-based waypoints for the trajectory plan based on the pose-based waypoints, and executing the task based on the joint-based waypoints for the trajectory plan.

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: 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: 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 method and simulation system for controlling at least one effector trajectory for solving a predefined task by at least one virtual effector. The method includes acquiring a sequence of postures to modify at least one of a contact constraint topology and an object constraint topology, generating a set of constraint equations based on at least one of the modified contact constraint topology and the modified object constraint topology, performing constraint relaxation on the generated set of constraint equations to generate a task description including the relaxed set of constraint equations, generating the effector trajectory by applying a trajectory generation algorithm on the generated task description, performing an inverse kinematics algorithm on the generated effector trajectory for generating a control signal, outputting the control signal to an output device, and generating, by the output device, image information displaying the effector trajectory of the virtual effector based on the control signal.

Abstract: A robot control method, and associated robot controllers and robots operating with such methods and controllers, providing real-time vibration suppression. The control method involves learning to support real-time, vibration-suppressing control. The method uses state-of-the-art machine learning techniques in conjunction with a differentiable dynamics simulator to yield fast and accurate vibration suppression. Vibration suppression using offline simulation approaches that can be computationally expensive may be used to create training data for the controller, which may be provide by a variety of neural network configurations. In other cases, sensory feedback from sensors onboard the robot being controlled can be used to provide training data to account for wear of the robot's components.

Abstract: An electronic apparatus is provided. The electronic apparatus includes a communicator comprising communication circuitry, a memory storing information on an artificial intelligence model, and a processor configured to: obtain a map generated based on sensing data obtained by an external electronic apparatus, simulate driving of the external electronic apparatus on the obtained map based on a plurality of parameter values and obtain driving result data for the plurality of parameter values, train the artificial intelligence model based on the plurality of parameter values and the obtained driving result data and obtain a plurality of parameter values related to driving of the external electronic apparatus, and control the communicator to transmit the plurality of obtained parameter values to the external electronic apparatus.

Abstract: A method of performing location teaching of a robotic arm includes maneuvering an end of arm tooling of a robotic arm to a predefined position of an interface object. The robotic arm is mounted within a mounting site of a mechanical mounting structure. The interface object is positioned on a sub-system of a medication dosing system that is mounted on the mechanical mounting structure. The interface object includes an alignment feature of a known size and shape. A sensor of the end of arm tooling is engaged with the interface object. An offset between the sensor and the interface object is determined based on an interaction between the sensor and the alignment feature. A position of the end of arm tooling is incremented with respect to the interface object along at least one axis. An actual position of the interface object is determined relative to the robotic arm.