US 12,331,479 B2
Systems, methods, and machines for automated screw anchor driving
Steven Kraft, Albany, CA (US); Jack West, San Rafael, CA (US); and Daniel Flanigan, Petaluma, CA (US)
Assigned to OJJO, INC., San Rafael, CA (US)
Filed by Ojjo, Inc., San Rafael, CA (US)
Filed on Oct. 11, 2021, as Appl. No. 17/498,743.
Application 17/498,743 is a continuation of application No. 17/091,523, filed on Nov. 6, 2020, granted, now 11,168,456.
Claims priority of provisional application 62/932,929, filed on Nov. 8, 2019.
Prior Publication US 2022/0064893 A1, Mar. 3, 2022
Int. Cl. E02D 7/22 (2006.01); E02D 5/56 (2006.01); E02D 33/00 (2006.01); H02S 20/10 (2014.01)
CPC E02D 7/22 (2013.01) [E02D 5/56 (2013.01); E02D 33/00 (2013.01); E02D 2600/10 (2013.01); H02S 20/10 (2014.12)] 6 Claims
OG exemplary drawing
 
1. A screw anchor driving machine comprising:
a movable mast, the mast comprising:
a first motor powering a drive train;
a rotary driver movable along the mast via the drive train;
a tool driver movable along the mast proximate to the rotary driver and operable to operate a tool through the rotary driver during a screw anchor driving operation; and
a second motor coupled to the tool driver for selectively moving the tool driver along the mast independent of the rotary driver;
a controller coupled to the first motor, the rotary driver, the tool driver, and the second motor to control the first motor, the rotary driver, the tool driver and the second motor to perform the automated screw anchor driving operation based on a control program stored in a memory of the controller; and
a plurality of sensors providing information to the controller during the automated screw anchor driving operation,
wherein the control program contains program code that causes the controller to calculate an upper leg length and an actual embedment depth based on a desired work point and minimum embedment depth, and to drive the screw anchor substantially to the actual embedment depth with at least the first motor, the rotary driver and the tool driver, based in part on information received from the plurality of sensors during the driving operation.