A collaborative robot cutting system for the assembly, construction, fabrication, and/or the completion of structural components for manufactured assemblies. A method of preparing work pieces and materials for further manufacturing operations employing the intuitive graphical interactive programming features of a robot cutting system user interface to enhance productivity and versatility in high mix, low volume fabrication environments with minimal operator training.

A robot for object manipulation may include sensors, a robot appendage, actuators configured to drive joints of the robot appendage, a planner, and a controller. Object path planning may include determining poses. Object trajectory optimization may include assigning a set of timestamps to the poses, optimizing a cost function based on an inverse kinematic (IK) error, a difference between an estimated required wrench and an actual wrench, and a grasp efficiency, and generating a reference object trajectory based on the optimized cost function. Grasp sequence planning may be model-based or deep reinforcement learning (DRL) policy based. The controller may implement the reference object trajectory and the grasp sequence via the robot appendage and actuators.

According to one embodiment, a wireless device comprises circuitry configured to generate a control signal of a control target, generate transfer necessity indicating whether transfer of the control signal is necessary or unnecessary, generate control information including the control signal and the transfer necessity, and transmit a wireless signal corresponding to the control information.

A tactile sensing system of a robot may include: a plurality of piezoelectric elements disposed at an object, and including a transmission (TX) piezoelectric element and a reception (RX) piezoelectric element; and at least one processor configured to: control the TX piezoelectric element to generate an acoustic wave having a chirp spread spectrum (CSS) at every preset time interval, along a surface of the object; receive, via the RX piezoelectric element, an acoustic wave signal corresponding to the generated acoustic wave; select frequency bands from a plurality of frequency bands of the acoustic wave signal; and estimate a location of a touch input on the surface of the object by inputting the acoustic wave signal of the selected frequency bands into a neural network configured to provide a touch prediction score for each of a plurality of predetermined locations on the surface of the object.

A method for picking and placing items includes the steps of: providing a picking conveyor transporting items to be picked; providing a placing conveyor to which the items are to be placed; and providing a plurality of robots configured to move the items from pick positions on the picking conveyor to place positions on the placing conveyor. For at least one of the plurality of robots there is defined an actual work area A.sub.ac that fulfils the condition A.sub.ac<A.sub.th−(A.sub.ol+A.sub.ex), wherein A.sub.th is a theoretical work area, A.sub.ol is an overlapping work area and A.sub.ex is an excessive work area of the respective robot. By limiting the actual work area A.sub.ac of the robots more than what is done conventionally, the total workload between the robots in pick and place systems may be balanced.

A control system includes a control apparatus and a plurality of robots. The control apparatus includes a function acquisition unit that acquires a function, a function form conversion unit that converts the function into a distributed calculable form, and a variable conversion unit that sets, based on the function which form is converted, variables to be stored by each of the robots and a process corresponding to the variables, to the robot. Each of the plurality of robots a consensus control means that updates a variable value stored by the robot itself based on the set variable while sending and receiving variable values among other communicable robots, and a function value inference means that infers a function value from the variable based on the set process.

A method includes moving a locating feature associated with a robotic arm of the robotic system along a selected defined path to a detected position, where the detected position is a position of the locating feature when a force feedback condition is satisfied. The method includes calculating a positional offset of the robotic arm based on a nominal position and the detected position of the robotic arm. The method includes performing, by the robotic system, one or more operations at the manufacturing station using the positional offset.

Methods and systems are provided for training machine learning (e.g., NN) or other artificial intelligence (AI) models to control a robot arm to manipulate a catheter to robotically perform an invasive clinical catheter-based procedure.

The invention relates to a mobile security basic control device (15) of a robot (1), comprising a hand-held housing (16), an emergency stop switching means (17) arranged at the housing (16), a communication device (18) for establishing a link in terms of control between the mobile security basic control device (15) and a robot controller (12) of the robot (1), and further comprising a holder (19) connected to the housing (16), which is designed to mount the mobile security basic control device (15) on a mobile terminal (20). Said mobile terminal has a terminal control system (21) and a multi-touchscreen (22), which is designed to transmit inputs to the terminal control system (21) via the multi-touchscreen (22). The mobile security basic control device (15) comprises a coding device (25) which, in a state where the mobile security basic control device (15) is mounted on the mobile terminal (20) by means of the holder (19), is designed to automatically transmit at least one identification code identifying the mobile security basic control device (15) to the terminal control system (21) via the multi-touchscreen (22).

In an embodiment, a method during execution of a motion plan by a robotic arm includes determining a voice command from speech of a user said during the execution of the motion plan, determining a modification of the motion plan based on the voice command from the speech of the user, and executing the modification of the motion plan by the robotic arm.