IP Library Granted Patent US 11,623,356
Granted Patent B2
US 11,623,356 · App. 17/712,563 · Granted Apr 11, 2023

Dynamic, interactive signaling of safety-related conditions in a monitored environment

Inventors: Clara Vu (Cambridge, MA); Scott Denenberg (Newton, MA); Abraham K. Feldman (Somerville, MA)
Assignee: VEO ROBOTICS, INC.
B25J19/061G08B3/00G08B5/36
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Quick Facts
Patent No.
US 11,623,356
App. No.
17/712,563
Granted
Apr 11, 2023
Kind
B2
Abstract

Systems and methods for determining safe and unsafe zones in a workspace—where safe actions are calculated in real time based on all relevant objects (e.g., some observed by sensors and others computationally generated based on analysis of the sensed workspace) and on the current state of the machinery (e.g., a robot) in the workspace—may utilize a variety of workspace-monitoring approaches as well as dynamic modeling of the robot geometry. The future trajectory of the robot(s) and/or the human(s) may be forecast using, e.g., a model of human movement and other forms of control. Modeling and forecasting of the robot may, in some embodiments, make use of data provided by the robot controller that may or may not include safety guarantees.

Claims (32)

1. A system for perceptibly indicating a condition associated with regions in a three-dimensional (3D) workspace including industrial machinery, the system comprising:

a plurality of sensors distributed about the workspace, each of the sensors being associated with a grid of pixels for recording images of a portion of the workspace within a sensor field of view;

a computer memory for storing (i) a plurality of images from the sensors and (ii) a model of the machinery and its permitted movements during performance of the activity; a source for generating perceptible signals; and

a processor configured to:

computationally generate, from the stored images, a 3D spatial representation of the workspace;

identify a first 3D region of the workspace corresponding to space occupied by the machinery within the workspace augmented by a 3D envelope around the machinery spanning the permitted movements in accordance with the stored model;

identify a second 3D region of the workspace corresponding to space occupied or potentially occupied, by a human within the workspace augmented by a 3D envelope around the human corresponding to anticipated movements of the human within the workspace within a predetermined future time; and

operate the signal source to perceptibly indicate the condition associated with the first and second regions.

2. The system of claim 1 , wherein the condition corresponds to a safety metric.

3. The system of claim 1 , wherein the condition has a degree corresponding to one of a plurality of colors.

4. The system of claim 3 , wherein the signal source is a plurality of differently colored lamps within the workspace.

5. The system of claim 3 , wherein the signal source is a plurality of differently colored tiles within the workspace.

6. The system of claim 3 , wherein the signal source is a 2D display.

7. The system of claim 3 , wherein the signal source is a VR/AR headset.

8. The system of claim 3 , wherein the condition is indicated by a color of a displayed minimum-distance line.

9. The system of claim 8 , wherein the condition is an anticipated condition.

10. The system of claim 9 , wherein the condition is whether a slowdown or a stop is necessary.

11. A method of perceptibly indicating a condition associated with regions in a three-dimensional (3D) workspace including industrial machinery, the workspace including a plurality of sensors distributed thereabout, each of the sensors being associated with a grid of pixels for recording images of a portion of the workspace within a sensor field of view, the method comprising the steps of:

computationally storing (i) a plurality of images from the sensors and (ii) a model of the machinery and its permitted movements during performance of the activity;

computationally generating, from the stored images, a 3D spatial representation of the workspace;

computationally identifying a first 3D region of the workspace corresponding to space occupied by the machinery within the workspace augmented by a 3D envelope around the machinery spanning the permitted movements in accordance with the stored model;

computationally identifying a second 3D region of the workspace corresponding to space occupied or potentially occupied, by a human within the workspace augmented by a 3D envelope around the human corresponding to anticipated movements of the human within the workspace within a predetermined future time; and

operating the signal source to perceptibly indicate the condition associated with the first and second regions.

12. The method of claim 11 , wherein the condition corresponds to a safety metric.

13. The method of claim 11 , wherein the condition has a degree corresponding to one of a plurality of colors.

14. The method of claim 12 , wherein the signal source is a plurality of differently colored tiles within the workspace.

15. The method of claim 13 , wherein the signal source is a plurality of differently colored lamps within the workspace.

16. The method of claim 13 , wherein the signal source is a 2D display.

17. The method of claim 13 , wherein the signal source is a VR/AR headset.

18. The method of claim 13 , wherein the condition is indicated by a color of a displayed minimum-distance line.

19. The method of claim 18 , wherein the condition is an anticipated condition.

20. The method of claim 19 , wherein the condition is whether a slowdown or a stop is necessary.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 4, 2024
From: VEO ROBOTICS, INC.
To: SYMBOTIC LLC
Reel/Frame 068839/0710 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 17, 2023
From: VU, CLARA; DENENBERG, SCOTT; FELDMAN, ABRAHAM K.
To: VEO ROBOTICS, INC.
Reel/Frame 062728/0053 →
Continuity (5)
Continuation 16919959 · Jul 2, 2020
Continuation In Part 15889767 · Feb 6, 2018
Provisional Application 62455834 · Feb 7, 2017
Provisional Application 62455828 · Feb 7, 2017
Related Publication 20220227013A1 · Jul 21, 2022
Cited By (1)
US 12,714,278