Granted Patent B2

US 12,748,823 · App. 19/447,579 · Granted Sep 29, 2026

Inventor: Armando Montalvo (Winter Garden, FL)

Assignee: Digital Global Systems, Inc.

G06F18/256B25J9/163B25J9/1694B60R19/483B60T8/1755B60T8/3275B60W10/18B60W10/184B60W30/085B60W30/09B60W60/00B60W60/0018B60W60/00186B62D15/0285G01C3/00G01C21/1652G01C21/3804G01C21/3811G01C21/3848G01C22/00G01S5/14G01S7/4808G01S11/00G01S13/08G01S13/103G01S13/42G01S15/08G01S15/101G01S15/42G01S17/08G01S17/88G01S17/894G05B13/0205G06F7/14G06F7/16G06F16/24G06F16/245G06F16/2455G06F16/24556G06F16/2456G06F16/33G06F16/334G06F16/43G06F16/53G06F16/903G06F16/90335G06F16/9035G06F17/18G06F18/217G06F18/2431G06F18/25G06F18/251G06N3/02G06N3/0464G06N5/022G06N5/042G06N5/045G06N5/046G06N5/048G06T7/521G06V10/764G06V10/803G06V10/82G06V20/56G08G1/0133G08G1/04G08G1/042H04L67/12H04W4/38B25J9/1664B60T2201/00B60T2201/03B60W2050/0052B60W2420/00B60W2420/40B60W2420/403B60W2420/408B60W2420/50B60W2510/069B60W2510/18B60W2520/04B60W2540/12B60W2554/801B60W2554/802B60W2556/35B60W2710/18B60W2754/30G01S2013/93185G05D2101/15G05D2111/50G05D2111/67G06F18/213G06N5/04G06N20/00G06T2207/10028G06T2207/20024G06T2207/20084G06T2207/30252G06T2207/30264G06V10/80G08B29/188

Abstract

Claims (47)

1 . A system for sensor data fusion for sensor management and utilization in robotics, comprising:

at least one computer processor including a memory;

at least one fusion engine, at least one inference engine, and at least one validation engine;

at least one first position sensor operable to capture a first position measurement of a robotic component; and

at least one second position sensor operable to capture a second position measurement of the robotic component;

wherein the at least one computer processor is operable to analyze the first position measurement and the second position measurement;

wherein the at least one fusion engine is operable to fuse the first position measurement and the second position measurement, and wherein the at least one inference engine is operable to determine at least one inference from the first position measurement and the second position measurement;

wherein the at least one inference engine is operable to determine a second inference;

wherein the at least one validation engine validates the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold; and

wherein the at least one computer processor is operable to instruct the robotic component.

2 . The system of claim 1 , wherein the predefined threshold includes the at least one inference being within about 4.5% or less of the second inference.

3 . The system of claim 1 , wherein the system is operable to store the first position measurement and the second position measurement after the at least one validation engine validates the at least one inference.

4 . The system of claim 1 , wherein the at least one validation engine is operable to validate the at least one inference passively and/or actively.

5 . The system of claim 4 , wherein passive validation includes not modifying a movement of the robotic component.

6 . The system of claim 4 , wherein active validation includes modifying at least one movement of the robotic component.

7 . The system of claim 1 , wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.

8 . A method for sensor data fusion for sensor management and utilization in robotics, comprising:

providing at least one computer processor including a memory;

providing at least one fusion engine, at least one inference engine, and at least one validation engine;

at least one first position sensor capturing a first position measurement of a robotic component;

at least one second position sensor capturing a second position measurement of the robotic component;

analyzing by the at least one computer processor the first position measurement and the second position measurement;

fusing by the at least one fusion engine the first position measurement and the second position measurement, and determining at least one inference by the at least one inference engine from the first position measurement and the second position measurement;

determining by the at least one inference engine a second inference;

validating by the at least one validation engine the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold; and

instructing by the at least one computer processor the robotic component based on the at least one inference being validated.

9 . The method of claim 8 , wherein the predefined threshold includes the at least one inference being within about 4.5% or less of the second inference.

10 . The method of claim 8 , further comprising validating the at least one inference passively and/or actively.

11 . The method of claim 10 , wherein validating passively includes not modifying a movement of the robotic component.

12 . The method of claim 10 , wherein validating actively includes modifying a movement of the robotic component.

13 . The method of claim 8 , further comprising adjusting via the at least one validation engine using artificial intelligence the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine.

14 . The method of claim 8 , further comprising storing the first position measurement and the second position measurement after the at least one validation engine validates the at least one inference.

15 . A system for sensor data fusion for sensor management and utilization in robotics, comprising:

at least one computer processor including a memory;

at least one fusion engine, at least one inference engine, and at least one validation engine; and

at least two sensors, each of the at least two sensors operable to measure a first position of a robotic component and a second position of the robotic component;

wherein the at least one computer processor is operable to analyze the first position and the second position;

wherein the at least one fusion engine is operable to fuse the first position and the second position, and wherein the at least one inference engine is operable to determine at least one inference from the first position and the second position;

wherein the at least one inference engine is operable to determine a second inference;

wherein the at least one validation engine validates the at least one inference when a comparison between the at least one inference and the second inference exceeds a predefined threshold;

wherein the at least one validation engine is operable to use artificial intelligence to dynamically adjust the predefined threshold based in part on types of data sources, environmental factors, and/or learning from previous analyses conducted by the at least one validation engine; and

wherein the at least one computer processor is operable to instruct the robotic component based on the at least one inference being validated.

16 . The system of claim 15 , wherein the predefined threshold includes the at least one inference being within about 4.5% or less of the second inference.

17 . The system of claim 15 , wherein the at least one validation engine is operable to validate the at least one inference passively and/or actively.

18 . The system of claim 17 , wherein passive validation includes not modifying a parameter.

19 . The system of claim 17 , wherein active validation includes modifying at least one parameter.

20 . The system of claim 15 , wherein the system is operable to store the first position and the second position after the at least one validation engine validates the at least one inference.

Continuity (6)

References Cited (248)