Some embodiments provide a user-friendly interface enabling a non-technical user to automatically provision a robotic process automation (RPA) environment on a target computing system such as a cloud computing platform or an on-premises server. The provisioned environment may include all necessary components (e.g., virtual machines, robots, robot orchestrator, databases, network links) to execute a robotic task. The provisioned environment is terminated automatically after or at a time specified by the user. The described systems and methods are particularly useful at trade shows or other events, in order to simplify and speed up the demonstration of RPA software capabilities to different customers planning RPA software deployment in different contexts, including on different cloud platforms or hybrid contexts combining cloud with on-premises host platforms.

Computerized robotic process automation (RPA) methods and systems that increase the flexibility and lower the cost with which RPA systems may be deployed are disclosed herein. In one embodiment, an RPA system and method avoids the need for preinstalled RPA software on a device employed by a user to create and/or execute software robots to perform RPA. In another embodiment, an RPA system and method provides a capability to execute software robots that may have been encoded in one or more programming languages to execute on an operating system different than that employed by a server of the RPA system.

A scanner controller analyzes a position instruction in which a position in a world coordinate system and a position in a local coordinate system of a path of laser light are associated with each other and creates a movement command for a drive unit of a scanner based on the position of the local coordinate system. Further, the scanner controller calculates the current position of the scanner in the local coordinate system based on the position and attitude of a robot in the world coordinate system and the position in the world coordinate system in accordance with the position instruction. When the distance between the calculated position of the local coordinate system and the position in the local coordinate system in accordance with the position instruction is below a predetermined threshold, the scanner controller then determines to start machining and performs control of a drive unit of the scanner.

A toy construction robotics system including a robotics control unit, the robotics control unit comprising: a housing comprising coupling elements configured for releasably interconnecting the robotics control unit with cooperating toy construction elements; a processor comprising programmed instructions; a plurality of I/O-ports connected to communicate with the processor; a plurality of separate light emitters arranged in a two-dimensional array on a front side of the housing, each of the light emitters being operable in response to instructions from the processor so as to produce at least two different indicator states; wherein the light emitters are aligned with respect to the I/O-ports such that each of the I/O-ports has an associated light emitter next to it. The light emitters may be operable, in response to instructions from the processor, to produce a machine readable code encoding data in respect of the robotics control unit. The machine readable code may comprise instructions for interaction between the robotics control unit and an external device.

Human-in-the-loop robot training using artificial intelligence (AI) for robotic process automation (RPA) is disclosed. This may be accomplished by a listener robot watching interactions of a user or another robot with a computing system. Based on the interactions by the user or robot with the computing system, the robot may be improved and/or personalized for the user or a group of users.

A robot control system includes robot controller circuitry that controls a robot, and host controller circuitry that communicates with the robot controller circuitry. The host controller circuitry further executes a control program, and transmits a command according to an execution result of the control program to the robot controller circuitry, and the robot controller circuitry further receives the command from the host controller circuitry, and executes pre-processing according to the command.

Embedded and/or pooled robotic process automation (RPA) robots are disclosed. A master robot initiates one or more RPA robots in a deterministic and/or probabilistic manner. For instance, when a step in an RPA workflow of the master robot is encountered where an action is not clear, some data is missing, there are multiple possible branches, etc., one or more embedded and/or pooled minion robots may be called upon by the master robot to determine the next action to take, to retrieve missing data, to determine which branch is appropriate, etc. The master robot may perform orchestration functionality with respect to the minion robot(s).

A scanner controller analyzes a position instruction in which a position in a world coordinate system and a position in a local coordinate system of a path of laser light are associated with each other and creates a movement command for a drive unit of a scanner based on the position of the local coordinate system. Further, the scanner controller calculates the current position of the scanner in the local coordinate system based on the position and attitude of a robot in the world coordinate system and the position in the world coordinate system in accordance with the position instruction. When the distance between the calculated position of the local coordinate system and the position in the local coordinate system in accordance with the position instruction is below a predetermined threshold, the scanner controller then determines to start machining and performs control of a drive unit of the scanner.

A system and a computer-implemented method for analyzing a robotic process automation (RPA) workflow are disclosed herein. The computer-implemented method may include obtaining the RPA workflow and analyzing the obtained RPA workflow to provide an analyzed RPA workflow. The computer-implemented method may further include determining one or metrics associated with the analyzed RPA workflow and performing one or more corrective activities for the analyzed RPA workflow based on the determined one or more metrics.

Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).