A program transfer system includes: a communication unit communicating with a robot and outputting a result of the communication; a determination unit checking a work program provided in the robot, based on the result of the communication, and determining whether to import a different target work program from the work program or not; a program import unit importing the target work program to the robot when the determination unit determines the importing; a collection unit collecting work data of complete work from the robot; and a program update unit performing machine learning using the work data collected by the collection unit, and updating the target work program, based on a result of the machine learning.

The invention relates to a system which comprises a workspace (3) storage module (5), at least one pointer (6) respectively associated with a gripper (4) of a robotic device (2), a module (8) for capturing the trajectory performed by the at least one pointer (6), a post-processing module (10) for determining a compatible trajectory of the one or more grippers (4), and a saving module (11), configured to save the compatible trajectory of each of the robotic devices (2).

Example robotic process automation systems and methods are described. In one implementation, a processing system receives one or more configuration options for a Bot, where the configuration options are associated with a design specification for the Bot. The processing system generates the Bot using the configuration options and instantiates the Bot on the processing system. A workflow associated with the design specification is executed by the Bot.

Example robotic process automation systems and methods are described. In one implementation, a processing system receives a first automation scenario, where the first automation scenario is for execution by the processing system. The processing system identifies a list of plugins in the first automation scenario and identifies a version number associated with each of the plugins in the first automation scenario. Additionally, the processing system verifies the list of plugins and their associated version numbers. If the list of plugins and their associated version numbers are verified, the processing system builds a first virtual environment for the plugins in the first automation scenario.

A method for interconnecting a first robot with at least one second robot (2, 21), each robot including at least: a first program, configured to pilot at least one communication equipment; a second program, the configuration of the second program being determined by a setup file including a field typ_service indicating a sending mode amongst the interpret or direct modes, a third program, configured to control at least one actuator and/or at least one sensor; the method comprising 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 comprising 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.

A sensorless collision detection method of robotic arm based on motor current includes acquiring an output current of a robotic arm joint motor; building a neural network, and using a backpropagation algorithm to update the weights and the deviations of the neural network to obtain an estimated current value; judging whether collision occurs by comparing the collision detection threshold with the error value between the output current of the robotic arm joint motor and the estimated output current of the neural network. The detection method is easy to operate and has higher universality.

An artificial intelligence problem is solved using an artificial intelligence memory graph data structure and a lexical database to identify supporting knowledge. A natural language input is received and classified into components. A starting node of an artificial intelligence memory graph data structure, which comprises one or more data nodes, is selected to begin a search for one or more supporting knowledge data nodes associated with the classified components. Starting at the starting node, the artificial intelligence memory graph data structure is searched using a lexical database to identify the one or more supporting knowledge data nodes. An artificial intelligence problem is identified and solved using the one or more identified supporting knowledge data nodes of the artificial intelligence memory graph data structure.

To perform a tool exchange in a medical robotic system, tool is retracted back into an entry guide from a deployed position and pose so that an assistant in the operating room may replace it with a different tool. While the tool is being retracted back towards the entry guide by user action, its configuration is changed to an entry pose while avoiding collisions with other objects so that it may fit in the entry guide. After the tool exchange is completed, a new tool is inserted in the entry guide and extended out of the guide by user action to the original position of the old tool prior to its retraction into the entry guide while the tool's controller assists the user by reconfiguring the new tool so as to resemble the original deployed pose of the old tool prior to its retraction into the entry guide.

A policy improvement method of improving a policy of reinforcement learning by a state value function, is executed by a computer and includes adding a plurality of perturbations to a plurality of components of a first parameter of the policy; estimating a gradient function of the state value function with respect to the first parameter, based on a result of an input determination performed for a control target in the reinforcement learning, the input determination being performed by using the policy that uses a second parameter obtained by adding the plurality of perturbations to the plurality of components; and updating the first parameter based on the estimated gradient function.

A method, system, and apparatus in the form of a robotic platform. When implemented as described, the method and system provide a highly flexible open platform for efficient and agile code development for robotic platforms through a cloud-based API. The method and system also allow developers to test new robotic platform programming immediately via the Internet and observe the results in real time, even for geographically remote robotic telepresence systems.