IP Library Granted Patent US 12,729,490
Granted Patent B2
US 12,729,490 · App. 18/157,600 · Granted Sep 8, 2026

System and method for automatically guiding a road construction machine

Inventors: Christopher Todd Avans (Sale Creek, TN); Ramon Pujol Guim (Chattanooga, TN)
Assignee: Roadtec, Inc.
E01C19/006E01C23/02E01C23/07E01C23/088E01C23/127E01C2201/08G05D1/248G05D3/20
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,729,490
App. No.
18/157,600
Filed
Jan 20, 2023
Granted
Sep 8, 2026
Kind
B2
Art Unit
3664
USPC
701/50
Abstract

A method and system for guiding a road construction machine using a machine guidance system comprising at least one each of a machine position sensor, a laser-based sensor, and a processing unit. The machine position sensor first measures a position of a road construction machine relative to a road boundary condition. The laser-based sensor then captures a series of scans corresponding to the boundary condition. The processing unit, using the scans, determines an ideal path of travel for the road construction machine. Based on the ideal travel path, the machine guidance system provides instructions to align the current travel path of the road construction machine to the ideal travel path.

Claims (50)

1 . A method for guiding a road construction machine along a desired travel path at a road-building site, the method comprising:

providing said road construction machine;

providing a machine guidance system (MGS) configured to provide instructions for aligning a current position of the road construction machine with the desired travel path at the road-building site in order to guide the road construction machine along the desired travel path, the MGS having:

one or more machine position sensors for determining the current position of the road construction machine;

one or more laser-based sensors that are each configured to capture a plurality of scans of a longitudinal boundary condition of a road surface along a longitudinal extent of the road surface; and

one or more processing units configured to:

identify at least one critical point in each of the plurality of scans that is estimated to correlate with a location of a reference point of the road surface,

generate a digital desired travel path of the road construction machine based on the at least one critical point of at least two of the plurality of scans; and

provide instructions for aligning the current position of the road construction machine with the desired travel path of the road construction machine, and

with the one or more machine position sensors, capturing the plurality of scans of the road surface at the road-building site, wherein the road surface has reference points disposed along the longitudinal extent of the road surface;

providing the plurality of scans to the one or more processing units of the MGS;

for each of the plurality of scans, identifying the at least one critical point using the one or more processing units;

with the one or more processing units, generating the digital desired travel path based on the at least one critical point of the at least two of the plurality of scans;

with the one or more machine position sensors, determining the current position of the road construction machine; and

with the one or more processing units, providing instructions for aligning the current position with the desired travel path.

2 . The method of claim 1 wherein the reference points are discontinuous along the longitudinal extent of the road surface such that a discontinuity exists between a first critical point of at least a first one of the plurality of scans and a second critical point of a second one of the plurality of scans that is immediately adjacent the first one of the plurality of scans.

3 . The method of claim 1 wherein the one or more processing units includes at least two preprogrammed edge profiles, wherein each of the at least two preprogrammed edge profiles corresponds to a different type of road-building site and includes a set of instructions for processing the plurality of scans of the road surface to identify the at least one critical point associated with the corresponding type of road-building site, the method further comprising the step of selecting one of the at least two preprogrammed edge profiles and identifying the at least one critical point based on the selected one of the at least two preprogrammed edge profiles.

4 . The method of claim 3 wherein the MGS is configured to automatically select one of the at least two preprogrammed edge profiles in response to an initial scan of the road surface, the method further comprising the step of using the one or more laser-based sensors to conduct an initial scan of the road surface such that, in response to the initial scan, the MGS automatically selects one of the at least two preprogrammed edge profiles.

5 . The method of claim 3 wherein the at least two preprogrammed edge profiles of the MGS utilize artificial intelligence in identifying the at least one critical point, generating the digital desired travel path based on the at least one critical point identified, determining the current position of the road construction machine, or providing instructions for aligning the current position of the road construction machine with the desired travel path.

6 . The method of claim 1 further comprising the step of using the one or more processing units to selectively utilize only a portion of the at least one critical points when generating the digital desired travel path.

7 . The method of claim 1 wherein the digital desired travel path and the instructions are updated in real-time as the road construction machine travels along the road surface.

8 . The method of claim 1 further comprising the steps of:

with a first sub-set of the one or more laser-based sensors, capturing a first plurality of scans of the road surface along a first longitudinal extent of the road surface along a first lateral side of the road construction machine;

with a second sub-set of the one or more laser-based sensors, capturing a second plurality of scans of the road surface along a second longitudinal extent of the road surface along a second lateral side of the road construction machine;

for each of the first plurality of scans, identifying a first critical point using the one or more processing units;

for each of the second plurality of scans, identifying a second critical point using the one or more processing units; and

generating the digital desired travel path based on the first critical point and the second critical point identified.

9 . The method of claim 1 further comprising the steps of:

with a first sub-set of the one or more laser-based sensors, capturing a first plurality of scans of the road surface along a longitudinal extent of the road surface along a first lateral side of the road construction machine;

with a second sub-set of the one or more laser-based sensors, capturing a second plurality of scans of the road surface along the longitudinal extent of the road surface along the first lateral side of the road construction machine;

for each of the first plurality of scans, identifying a first critical point using the one or more processing units;

for each of the second plurality of scans, identifying a second critical point using the one or more processing units; and

generating the digital desired travel path based on the first critical point and the second critical point identified.

10 . The method of claim 9 wherein each of the second critical points is different from each of the first critical points.

11 . A machine guidance system (MGS) configured to provide instructions for aligning a current position of a road construction machine with a desired travel path at a road-building site in order to guide the road construction machine along the desired travel path, the MGS comprising:

one or more machine position sensors for determining the current position of the road construction machine;

one or more laser-based sensors that are each configured to capture a plurality of scans of a longitudinal boundary condition of a road surface along a longitudinal extent of the road surface; and

one or more processing units configured to:

identify at least one critical point in each of the plurality of scans that is estimated to correlate with a location of a reference point of the road surface;

generate a digital desired travel path of the road construction machine based on the at least one critical point of at least two of the plurality of scans; and

provide instructions for aligning the current position of the road construction machine with the desired travel path of the road construction machine.

12 . The MGS of claim 11 wherein the one or more machine position sensors are further configured to determine at least one of a current heading or a current speed of the road construction machine.

13 . The MGS of claim 11 wherein the one or more processing units are further configured to generate a line that is fitted to the at least one critical point of at least two of the plurality of scans identified and wherein the desired travel path is generated based on the line and wherein the desired travel path and the instructions for aligning the current position of the road construction machine with the desired travel path are based on at least one parameter related to the road construction machine, wherein the at least one parameter is selected from a group consisting of: a geometry of the road construction machine or a component or portion thereof, a current speed of the road construction machine, and a current heading of the road construction machine.

14 . The MGS of claim 13 wherein the one or more processing units is configured to generate the line based on a curve best approximating a theoretical line connecting the at least one critical point of at least two of the plurality of scans.

15 . The MGS of claim 11 wherein the one or more processing units are further configured to automatically execute the instructions so as to automatically align the road construction machine with the desired travel path including by automatically steering the road construction machine.

16 . The MGS of claim 11 wherein the one or more processing units include a selection of at least two preprogrammed edge profiles, wherein each of the at least two preprogrammed edge profiles corresponds to a different type of road-building site and includes a set of instructions for processing the plurality of scans of the road surface to identify at least one critical point in each of the plurality of scans associated with the corresponding type of road-building site.

17 . The MGS of claim 16 wherein the MGS is configured to automatically select one of the at least two preprogrammed edge profiles in response to an initial scan of the road surface.

18 . The MGS of claim 11 wherein the at least one processing unit is configured to generate a representative model of the road surface that includes a desired function path for performing a desired machine function relative to the road surface and, upon generation of the representative model, to provide instructions for positioning the road construction machine such that the desired machine function may be performed along the desired function path.

19 . The MGS of claim 11 further comprising a controller configured to receive the instructions for aligning the current position of the road construction machine with the desired travel path of the road construction machine and to automatically adjust the position of the road construction machine via an automatic steering control device, such that the road construction machine travels along the desired travel path.

20 . The MGS of claim 11 wherein the MGS is disposed exclusively on the road construction machine.

Assignments (2)
SECURITY AGREEMENT Recorded Jul 2, 2025
From: ASTEC INDUSTRIES, INC.; ASTEC, INC.; ASTEC MOBILE SCREENS, INC.; BREAKER TECHNOLOGY, INC.; CARLSON PAVING PRODUCTS, INC.; JOHNSON CRUSHERS INTERNATIONAL, INC.; KOLBERG-PIONEER, INC.; POWER FLAME INCORPORATED; ROADTEC, INC.; TELSMITH, INC.; TERRASOURCE GLOBAL CORPORATION; CMI/CSI LLC; TABOR MACHINE COMPANY, LLC; ELGIN POWER AND SEPARATION SOLUTIONS, LLC; ELGIN SEPARATION SOLUTIONS INDUSTRIALS, LLC
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS ADMINISTRATIVE AGENT
Reel/Frame 071787/0859 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 20, 2023
From: GUIM, RAMON PUJOL; AVANS, CHRISTOPHER TODD
To: ROADTEC, INC.
Reel/Frame 062442/0432 →
Continuity (2)
Provisional Application 63397420 · Aug 12, 2022
Related Publication 20240052583A1 · Feb 15, 2024
References Cited (41)
US 6371566B1 · Haehn · 2002 [cited by applicant]
US 6799922B2 · Smith · 2004 [cited by applicant]
US 7399139B2 · Kieranen et al. · 2008 [cited by applicant]
US 10007270B2 · Mazur et al. · 2018 [cited by third party]
US 10480939B2 · Annovi et al. · 2019 [cited by applicant]
US 10633803B2 · Højland · 2020 [cited by examiner]
US 10829898B2 · Morrison · 2020 [cited by applicant]
US 11725348B2 · Nelson · 2023 [cited by examiner]
US 11834797B2 · Nelson · 2023 [cited by examiner]
US 20060198700A1 · Maier et al. · 2006 [cited by third party]
US 20160060820A1 · Berning et al. · 2016 [cited by applicant]
US 20180023260A1 · Muir et al. · 2018 [cited by applicant]
US 20180106014A1 · Horstman et al. · 2018 [cited by applicant]
US 20190332082A1 · Wright et al. · 2019 [cited by applicant]
US 20210010210A1 · Ellwein · 2021 [cited by examiner]
US 20210247514A1 · Horn · 2021 [cited by examiner]
US 20210310202A1 · Doy et al. · 2021 [cited by applicant]
US 20210317620A1 · Buschmann et al. · 2021 [cited by applicant]
US 20210388564A1 · Hirman et al. · 2021 [cited by applicant]
US 20220259827A1 · Argenziano et al. · 2022 [cited by applicant]
US 20220290383A1 · Buschmann · 2022 [cited by examiner]
US 20240052583A1 · Avans · 2024 [cited by examiner]
AU 2023208196A1 · 2024 [cited by examiner]
CA 3207671A1 · 2024 [cited by examiner]
CN 107314768B · 2020 [cited by examiner]
CN 111845709A · 2020 [cited by examiner]
CN 113260876A · 2021 [cited by examiner]
DE 9313075U1 · 1993 [cited by applicant]
DE 19951296C2 · 1999 [cited by third party]
DE 19951297C1 · 1999 [cited by third party]
EP 1118713A1 · 2000 [cited by third party]
EP 3524731B1 · 2021 [cited by examiner]
EP 4056758A1 · 2022 [cited by examiner]
JP 6386794B2 · 2018 [cited by examiner]
KR 102247300B1 · 2021 [cited by examiner]
WO WO2020088782A1 · 2020 [cited by examiner]
Edward Johnson, Laser Guided Screed Machine, (Year: 2019). [cited by examiner]
Wang, Yuchen, et al. “Automatic extraction and evaluation of pavement three-dimensional surface texture using laser scanning technology.” Automation in construction 141: 104410. (Year: 2022). [cited by examiner]
De Soto, Borja Garcia, and Miroslaw J. Skibniewski. “Future of robotics and automation in construction.” Construction 4.0. Routledge, 2020. 289-306. [cited by examiner]
Loizou, L., Barati, K., Shen, X., & Li, B. Quantifying advantages of modular construction: Waste generation. Buildings, 11(12), 622. ( Year: 2021). [cited by examiner]
Non-Final Office Action for U.S. continuation-in-part U.S. Appl. No. 18/962,611, dated Jun. 2, 2026, 8 pages. [cited by applicant]