One variation of a method for autonomously scanning and processing a part includes: accessing a part model representing a part positioned in a work zone adjacent a robotic system; retrieving a sanding head translation speed; retrieving a toolpath for execution on the part defining positions, orientations, and target forces applied by the sanding head to the part. The method includes traversing the sanding head along the toolpath, at the sanding head translation speed; reading a sequence of applied forces from a force sensor coupled to the sanding head at positions along the toolpath; and deviating from the toolpath to maintain the set of applied forces within a threshold difference of a sequence of target forces along the toolpath. In one variation of the method, the robotic system executes a toolpath at a duration less than target duration by selectively varying target force and sanding head translation speed across the part.

The present disclosure provides a grip manipulator used in a robot to eliminate an inefficient and power consumable operation caused by the use of multiple manipulators when gripping an object or handling the gripped object. The grip manipulator includes a manipulator body, a support rod of a first group and a support rod of a second group provided to protrude from the manipulator body in a direction, a longitudinal drive unit configured to discharge or introduce the support rod of the first group or the support rod of the second group in the protruding direction, and a transverse drive unit configured to spread or gather the support rod of the first support group or the support rod of the second group in a direction perpendicular to the protruding direction.

An interactive autonomous robot is configured for deployment within a social environment. The disclosed robot includes a show subsystem configured to select between different in-character behaviors depending on robot status, thereby allowing the robot to appear in-character despite technical failures. The disclosed robot further includes a safety subsystem configured to intervene with in-character behavior when necessary to enforce safety protocols. The disclosed robot is also configured with a social subsystem that interprets social behaviors of humans and then initiates specific behavior sequences in response.

A machine learning device that searches for a first parameter of a component of a servo control device that controls a servo motor includes: a solution detection unit that acquires a set of evaluation function values used during machine learning or after machine learning, plots the set of evaluation function values in a search range of the first parameter or a second parameter used for searching for the first parameter, and detects whether a search solution is at an edge of the search range or is in a predetermined range from the edge; and a range changing unit that changes the search range to a new search range of the first parameter or the second parameter based on the estimation made on evaluation function values of an evaluation function expression when the search solution is at the edge of the search range or is in the predetermined range.

Task automation by support robots for robotic process automation (RPA) is disclosed. RPA robots may be located on the computing systems of two or more users and/or remotely. The RPA robots may use an artificial intelligence (AI)/machine learning (ML) model that is trained to use computer vision (CV) to recognize tasks that the respective user is performing with the computing system. The RPA robots may then determine that the respective user is performing certain tasks on a regular basis in response to a certain action, such as receiving a request via email or another application, determining that a certain task has been completed, noting that a time period has elapsed, etc., and automate the respective tasks.

The invention relates generally to a method and system that provides robust metric reporting based on analysis of computer vision derived-video data. The invention utilizes learning-based methods for object identification, object localization, and contextual analysis in order to generate insights into, for example, efficiency, productivity, design and planning, and health and safety compliance in a workflow environment.

A system and method for sequence extraction using screenshot images to generate a robotic process automation workflow is disclosed. The system and method include capturing a plurality of screenshots of steps performed by a user on an application using a processor, storing the screenshots in memory, determining action clusters from the captured screenshots by randomly clustering actions into an arbitrary predefined number of clusters, wherein screenshots of different variations of a same action is labeled in the clusters, extracting a sequence from the clusters, and discarding consequent events on the screen from the clusters, and generating an automated workflow based on the extracted sequences.

A Computer Vision (CV) model generated by a Machine Learning (ML) system may be retrained for more accurate computer image analysis in Robotic Process Automation (RPA). A designer application may receive a selection of a misidentified or non-identified graphical component in an image form a user, determine representative data of an area of the image that includes the selection, and transmit the representative data and the image to an image database. A reviewer may execute the CV model, or cause the CV model to be executed, to confirm that the error exists, and if so, send the image and a correct label to an ML system for retraining. While the CV model is being retrained, an alternative image recognition model may be used to identify the misidentified or non-identified graphical component.

A system and a method predict a collision free posture of a kinematic system. The method includes: receiving a 3D virtual environment, receiving a 3D representation of the kinematic system and a set of 3D postures defined for the 3D virtual kinematic system, receiving a target task to be performed by the kinematic system with respect to the surrounding environment, and receiving a prescribed location within the 3D virtual environment. The prescribed location defines a position at which the 3D virtual kinematic system has to be placed within the 3D virtual environment. A collision free detection function (CFD) is applied to a set of input data containing the 3D virtual environment, the target task, the prescribed location and the set of postures. The CFD function outputs a set of collision free postures enabling the kinematic system to perform the target task when located at the prescribed location.

A decoupling control method for a humanoid robot includes: decomposing tasks of the humanoid robot to obtain kinematic tasks and dynamic tasks, and classifying corresponding joints of the humanoid robot into kinematic task joints or dynamic task joints; solving desired positions and desired speeds of the kinematic task joints for performing the kinematic tasks according to desired positions and desired speeds of ends in the kinematic tasks using inverse kinematics; calculating torques of the kinematic task joints based on the desired positions and desired speeds of the kinematic task joints; and solving a pre-built optimization model of torques required for the dynamic task joints based on the calculated torques of the kinematic task joints, to obtain torques required by the dynamic task joints for performing the dynamic tasks.