A method for operating a machine control system and a corresponding machine control system uses a portable hand-held terminal for functionally influencing at least one machine controller. The terminal includes at least one emergency stop actuation element for terminating potentially dangerous machine operations. The controller and/or the terminal is adapted for indicating a representation of the control system on the terminal display. The controller and/or the hand-held terminal is adapted for indicating the operational range(s) of the at least one emergency stop actuation element by the terminal display. The controller and/or the hand-held terminal are further adapted for simultaneously representing the operational range(s) of the at least one emergency stop actuation element by selective, fail-safe controlling of at least one lighting device at the hand-held terminal and/or at least one discrete lighting device in or at the at least one emergency stop actuation element at the hand-held terminal.

Training and/or using both a high-level policy model and a low-level policy model for mobile robot navigation. High-level output generated using the high-level policy model at each iteration indicates a corresponding high-level action for robot movement in navigating to the navigation target. The low-level output generated at each iteration is based on the determined corresponding high-level action for that iteration, and is based on observation(s) for that iteration. The low-level policy model is trained to generate low-level output that defines low-level action(s) that define robot movement more granularly than the high-level action—and to generate low-level action(s) that avoid obstacles and/or that are efficient (e.g., distance and/or time efficiency).

A control system 1 includes a first controller, and a second controller. The second controller includes a program storage module that stores two or more coordinate conversion programs, and a control processing module 240 that acquires program designation information for designating one of two or more coordinate conversion programs from the first controller. Additionally, the control processing module may acquire a first operation command in the coordinate system for the first controller from the first controller, and convert the first operation command to an operation target value of two or more joint axes of a multi-axis robot using the coordinate conversion programs according to the program designation information. Driving power according to the operation target value may be output to the joint axes.

Methods, apparatus, and computer-readable media for determining and utilizing human corrections to robot actions. In some implementations, in response to determining a human correction of a robot action, a correction instance is generated that includes sensor data, captured by one or more sensors of the robot, that is relevant to the corrected action. The correction instance can further include determined incorrect parameter(s) utilized in performing the robot action and/or correction information that is based on the human correction. The correction instance can be utilized to generate training example(s) for training one or model(s), such as neural network model(s), corresponding to those used in determining the incorrect parameter(s). In various implementations, the training is based on correction instances from multiple robots. After a revised version of a model is generated, the revised version can thereafter be utilized by one or more of the multiple robots.

An electronic apparatus for a database construction and control of a robotic manipulator is provided. The electronic apparatus stores information associated with a task of a robotic manipulator. The electronic apparatus further receives a first plurality of signals from a first plurality of sensors associated with a wearable device. The electronic apparatus further applies a predefined model on a first set of signals of the first plurality of signals. The electronic apparatus further determines arrow direction information based on the application of the predefined model on the first set of signals. The electronic apparatus further aggregates the determined arrow direction information with information about the first set of signals to generate output information. The electronic apparatus further stores the generated output information for each of a first plurality of poses performed for the task using the wearable device.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for rule execution in an online robotics system. One of the systems includes an execution engine subsystem and an execution memory subsystem. The execution engine receives rules having types and subtypes that represent a particular entity in an operating environment of a robot, provides subscription requests to the execution memory subsystem, and receives events emitted by the execution memory subsystem. The an execution memory receives subscription requests from the execution engine subsystem, receives new observations, converts the new observations into fact updates, performs pattern matching with the fact updates against the patterns of the subscription requests, and emits events to the execution engine subsystem for patterns that have been matched by the fact updates.

A method and dynamic learning system for providing dynamic cross learning is disclosed. The dynamic learning system identifies one or more changes in an environment in which an automated task performing device is scheduled to perform one or more activities. The dynamic learning system initiates a dynamic learning associated with the one or more changes for the automated task performing device based on pre-stored contextual information. Based on the dynamic learning, one or more actions is provided to the automated task performing device to perform the one or more activities in view of the one more changes. Therefore, the present disclosure facilitates dynamic determination and analysis of environment and situation for the automated task performing device for performing the activities. Thus, leading to dynamic decision-making to provide adjustment to the automated task performing device in any situation.

A robot system includes: a robot; a plurality of operation terminals that receive an input of a password for acquiring operation authority of the robot and an operation input for operating the robot from a user; and a robot controller communicable with the operation terminals . The robot controller drives, in a controlled manner, the robot according to operation from a single operation terminal among the operation terminals . The robot controller includes a password storage unit that stores a password for granting operation authority of the robot to the operation terminal . The robot controller further includes an operation authority grant processing unit that grants operation authority of the robot to a single operation terminal to which a proper predetermined password stored in the password storage unit is first input in a state in which operation authority of the robot is not granted to any operation terminal.

Systems and a method for teaching a robot in reaching a given target location. The system and method include receiving inputs on a representation of a given target location to be reached by the robot. A check is made whether the given target location is singular. If the given target location is non-singular, the teaching of the robot is effected by associating with the given target location a selected configuration. If the given target is singular, the teaching of the robot is effected by associating with the given target location an assigned joint-values solution.

An autoteach enclosure system includes a plurality of surfaces that at least partially enclose an interior volume of the autoteach enclosure system. The autoteach enclosure system further includes an autoteach pin at least partially disposed within the interior volume. The autoteach pin is a scannable feature having a fixed position within the autoteach enclosure system. The autoteach enclosure system further includes a front interface coupled to one or more of the plurality of surfaces to interface the autoteach enclosure system with a substantially vertical portion of a load port of a wafer processing system. The autoteach pin enables an autoteach operation of a robot arm of the wafer processing system. The autoteach operation is an operation to automatically teach the fixed position within the autoteach enclosure system to the robot arm of the wafer processing system.