Veo Robotics, Inc.

Symbotic LLC

Gene Malkin

Scott A Denenberg

Lev Persits

Valentina Chamorro

Clara Vu

Alberto Moel

Patrick Sobalvarro

Robert Craig Randall

Marek Wartenberg

Pratik Devendra Dalvi

Ilya A Kriveshko

Paul Jakob Schroeder

Systems and methods utilize one or more 3D cameras (e.g., ToF cameras) in industrial safety applications. The 3D camera generates a depth map that may be used by external hardware and software to classify objects in a workcell and generate control signals for machinery. To facilitate sensor-specific calibration and coordination among sensors in a workcell, the sensors may store calibration data in a boot file that is loaded upon start-up. During initialization, the calibration data is loaded and, as the sensor operates, corrections are made to sensed data (e.g., pixel depth values) using the calibration data.

Calibration of depth-sensing computer vision systems

In various embodiments, systems and methods for acquiring depth images utilize an architecture suited to safety-rated applications, and may include more than sensor (such as time-of-flight sensors) operating along different optical paths and a comparison module for ensuring proper sensor operation. Error metrics may be associated with pixel-level depth values for purposes of allowing safe control based on imperfectly known depths.

Depth-sensing computer vision system

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

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

Systems and methods for calibrating a sensor array for 3D depth sensing include the steps of providing multiple 3D sensors each for (i) illuminating a field of view of the sensor and (ii) generating an output array of pixelwise values indicative of distances to objects within the illuminated a field of view; sequentially causing each of the 3D sensors to generate an output array while other 3D sensors are illuminating their fields of view; and creating an interference matrix from the generated output arrays, the interference matrix indicating, for each of the 3D sensors, a degree of interference by other 3D sensors simultaneously active therewith.

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Brookline, MA, United States of America

Gene Malkin