3m Innovative Properties Company

Veo Robotics, Inc.

Midmark Corporation

Ilya A Kriveshko

Scott A Denenberg

Clara Vu

David E Altobelli

Douglas P Hart

Janos Rohaly

Alberto Moel

Paul Jakob Schroeder

Patrick Sobalvarro

Eric B Paley

Edward K Tekeian

Dmitriy A Dedkov

Lev Persits

Micah J Rosenbloom

Robert N Nazzal

Steven V Weeks

Marek Wartenberg

Patrick Joseph Foy

Dmitriy Dedkov

Elliot Simon

Justin Bronder

Valentina Chamorro

Gene Malkin

Joseph Boerjes

Robert Craig Randall

James H McQueston

Benjamin Frantzdale

Joseph Boeries

Patrick J Foy

Zeynep Şeker

Paul Jacob Schroeder

Steven J Weeks

Systems and methods for identifying a robot end effector in a processing environment may utilize one or more sensors for digitally recording visual information and providing that information to an industrial workflow. The sensor(s) may be positioned to record at least one image of the robot including the end effector. A processor may determine the identity of the end effector from the recorded image(s) and a library or database stored digital models.

Robot end-effector sensing and identification

Systems and methods for continuously monitoring a workcell during operation of industrial machinery are disclosed. The system may comprise a safety system that includes at least one sensor and supporting software and/or hardware for acquiring image data associated with the workcell; a monitoring system for detecting a parameter value associated with the safety system; and a controller configured to determine a status of the safety system based at least in part on the detected parameter value and cause an alert to be issued if the status of the safety system does not satisfy a target objective.

Continuous monitoring of a workcell safety system

An integrated system and method for monitoring a workspace, classifying regions therein, dynamically identifying safe states, and identifying and tracking workpieces utilizes semantic analysis of a robot in the workspace and identification of the workpieces with which it interacts, as well as a semantic understanding of entity properties both governing and arising from interaction with other entities for control purposes. These properties may be stored in a profile corresponding to the entity; depending on the implementation, the profile and methods associated with the entity may be stored in a data structure corresponding to the entity 'class.' Volumetric regions (e.g., voxels) corresponding to each entity may be tracked and used to implement object methods and/or control methods. For example, machinery may be controlled in accordance with the attributes specified by the objects corresponding to identified entities in a monitored workspace.

Workplace monitoring and semantic entity identification for safe machine operation

Control systems for industrial machinery (e.g., robots) or other devices such as medical devices utilize a safety processor (SP) designed for integration into safety applications and computational components that are not necessarily safety-rated. The SP monitors performance of the non-safety computational components, including latency checks and verification of identical outputs. One or more sensors send data to the non-safety computational components for sophisticated processing and analysis that the SP cannot not perform, but the results of this processing are sent to the SP, which then generates safety-rated signals to the machinery or device being controlled by the SP. As a result, the system may qualify for a safety rating despite the ability to perform complex operations beyond the scope of safety-rated components.

System architecture for safety applications

Various embodiments for enforcing safe operation of machinery performing an activity in a three-dimensional (3D) workspace includes computationally generating a 3D spatial representation of the workspace; computationally mapping 3D regions of the workspace corresponding to space occupied by the machinery and a human; and based thereon, restricting operation of the machinery in accordance with a safety protocol during physical performance of the activity. Limited-access zones are defined within which the presence of a human will not affect operation of the machinery.

Context-sensitive safety monitoring of collaborative work environments

Various approaches to ensuring safe operation of industrial machinery in a workcell include disposing multiple image sensors proximate to the workcell and acquiring, with at least some of the image sensors, the first set of images of the workcell; registering the sensors to each other based at least in part on the first set of images and, based at least in part on the registration, converting the first set of images to a common reference frame of the sensors; determining a transformation matrix for transforming the common reference frame of the sensors to a global frame of the workcell; registering the sensors to the industrial machinery; acquiring the second set of images during operation of the industrial machinery; and monitoring the industrial machinery during operation thereof based at least in part on the acquired second plurality of images, transformation, and registration of the sensors to the industrial machinery.

Systems and methods for automatic sensor registration and configuration

A three-dimensional model of an object is employed to aid in navigation among a number of images of the object taken from various viewpoints. In general, an image of an object such as a digital photograph is displayed in a user interface or the like. When a user selects a point within the display that corresponds to a location on the surface of the object, another image may be identified that provides a better view of the object. In order to maintain user orientation to the subject matter while navigating to this destination viewpoint, the display may switch to a model view and a fly-over to the destination viewpoint may be animated using the model. When the destination viewpoint is reached, the display may return to an image view for further inspection, marking, or other manipulation by the user.

Navigating among images of an object in 3D space

Tools are described for preparing digital dental models for use in dental restoration production processes, along with associated systems and methods. Dental modeling is improved by supplementing views of three-dimensional models with still images of the modeled subject matter. Video data acquired during a scan of the model provides a source of still images that can be displayed alongside a rendered three-dimensional model, and the two views (model and still image) may be synchronized to provide a common perspective of the model's subject matter. This approach provides useful visual information for disambiguating surface features of the model during processing steps such as marking a margin of a prepared tooth surface for a restoration. Interactive modeling tools may be similarly enhanced. For example, tools for margin marking may synchronize display of margin lines between the still image and the model so that a user can interact with either or both of the visual representations, with changes to a margin reflected in both displays.

Video-assisted margin marking for dental models

A three-dimensional measurement is refined by warping two-dimensional images of an object from offset camera positions according to a three-dimensional model of the object, and applying any resulting discrepancies to refine the three-dimensional model, or to refine one of a number of three-dimensional measurements used to create the three-dimensional model.

Three-dimensional model refinement

Video data acquired during a three-dimensional scan of dentition provides a source of still images that can be displayed alongside a rendered three-dimensional model of the dentition, and the two views (model and still image) may be synchronized to provide a common perspective of the model's subject matter. This approach provides useful visual information for disambiguating surface features of the model during interactive model processing steps such as marking a margin of a prepared tooth surface for a restoration.

Synchronized views of video data and three-dimensional model data

Three-dimensional scanning is improved with the use of space carving to exclude certain scan results from processing and display. Using space carving techniques, a spatial matrix is maintained to store data on volumetric regions (or voxels) known to be empty. By excluding or modifying processing of outlier data from within these unoccupied voxels, a three-dimensional reconstruction process can achieve concurrent improvements in accuracy and speed. In addition, a real time display of scan results can be improved by modifying how such outliers are rendered.

Space carving in 3D data acquisition

Growing community of inventors

Littleton, MA, United States of America

Ilya A Kriveshko