Veo Robotics, Inc.

Marek Wartenberg

Clara Vu

Scott A Denenberg

Alberto Moel

Brad C Mello

Patrick Sobalvarro

Ilya A Kriveshko

Lev Persits

Paul Jakob Schroeder

Valentina Chamorro

Gene Malkin

Matthew Galligan

Pratik Devendra Dalvi

Nicole Aucoin

Zeynep Şeker

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

Crosstalk mitigation among cameras in neighboring monitored workcells is achieved by computationally defining a noninterference scheme that respects the independent monitoring and operation of each workcell. The scheme may involve communication between adjacent cells to adjudicate non-interfering camera operation or system-wide mapping of interference risks and mitigation thereof. Mitigation strategies can involve time-division and/or frequency-division multiplexing.

Crosstalk mitigation for multi-cell workspace monitoring

Embodiments of the present invention provide automated robotic system identification and stopping time and distance estimation, significantly improving on existing ad-hoc methods of robotic system identification. Systems and methods in accordance herewith can be used by end users, system integrators, and the robot manufacturers to estimate the dynamic parameters of a robot on an application-by-application basis.

System identification of industrial robot dynamics for safety-critical 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 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.

Safe operation of machinery using potential occupancy envelopes

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Westbrook, ME, United States of America

Marek Wartenberg