Grade Control Cleanup Pass Using Cost Optimization

Abstract

A computer-implemented method for determining a cleanup pass profile for a machine implement is provided. The method may include identifying a pass target extending from a first end to a second end along a work surface, determining a plurality of primitives of a cleanup pass profile extending between the first end and the second end where each primitive may be defined based at least partially on volume constraints, determining a cost value associated with moving the machine implement along the cleanup pass profile based on an optimization cost function, and adjusting the volume constraints associated with one or more of the primitives to minimize the cost value.

What is claimed is: 
     
         1 . A computer-implemented method for determining a cleanup pass profile for a machine implement, comprising:
 identifying a pass target extending from a first end to a second end along a work surface;   determining a plurality of primitives of a cleanup pass profile extending between the first end and the second end, each primitive being defined based at least partially on volume constraints;   determining a cost value associated with moving the machine implement along the cleanup pass profile based on an optimization cost function; and   adjusting the volume constraints associated with one or more of the primitives to minimize the cost value.   
     
     
         2 . The computer-implemented method of  claim 1 , wherein the optimization cost function is configured to associate the cost value of the cleanup pass profile with one or more parameters including curvature, curvature limit, slope, slope limit, implement load, implement load average, maximum implement load limit, minimum implement load limit, crest volume, cut depth relative to pass target, cut depth relative to work surface, and volume differential between the pass target and the work surface. 
     
     
         3 . The computer-implemented method of  claim 2 , wherein the optimization cost function is configured to increment the cost value for each parameter that exceeds a corresponding target threshold. 
     
     
         4 . The computer-implemented method of  claim 2 , wherein each of the parameters is weighted by the optimization cost function according to its relevance to the cost value. 
     
     
         5 . The computer-implemented method of  claim 1 , wherein the volume constraints associated with one or more of the primitives are adjusted using one or more of gradient descent algorithms, genetic algorithms, and Nelder-Mead algorithms. 
     
     
         6 . The computer-implemented method of  claim 1 , wherein a total volume differential between the work surface and the cleanup pass profile is maintained during adjustments. 
     
     
         7 . The computer-implemented method of  claim 1 , wherein an elevation and a slope of each endpoint of each primitive are maintained during adjustments. 
     
     
         8 . The computer-implemented method of  claim 1 , further adjusting one or more of an elevation at one or more endpoints of the primitives, a location of one or more of the endpoints, and a number of the endpoints. 
     
     
         9 . A control system for determining a cleanup pass profile for a machine implement, comprising:
 a memory, the memory being a non-transitory computer-readable storage medium, configured to retrievably store one or more algorithms; and   a controller in communication with the memory and, based on the one or more algorithms, configured to at least:   identify a pass target extending from a first end to a second end along a work surface,   determine a plurality of primitives of a cleanup pass profile extending between the first end and the second end,   determine a cost value associated with moving the machine implement along the cleanup pass profile based on an optimization cost function, and   adjust volume constraints associated with one or more of the primitives to minimize the cost value.   
     
     
         10 . The control system of  claim 9 , wherein the controller associates the cost value of the cleanup pass profile with one or more parameters of the optimization cost function including curvature, curvature limit, slope, slope limit, implement load, implement load average, maximum implement load limit, minimum implement load limit, crest volume, cut depth relative to pass target, cut depth relative to work surface, and volume differential between the pass target and the work surface. 
     
     
         11 . The control system of  claim 10 , wherein the controller increments the cost value for each parameter of the optimization cost function that exceeds a corresponding target threshold. 
     
     
         12 . The control system of  claim 10 , wherein the controller assigns a weight to each of the parameters of the optimization cost function according to its relevance to the cost value. 
     
     
         13 . The control system of  claim 9 , wherein the controller adjusts the volume constraints associated with one or more of the primitives using one or more of gradient descent algorithms, genetic algorithms, and Nelder-Mead algorithms. 
     
     
         14 . The control system of  claim 9 , wherein the controller maintains a total volume differential between the work surface and the cleanup pass profile during adjustments. 
     
     
         15 . The control system of  claim 9 , wherein the controller maintains an elevation and a slope of each endpoint of each primitive during adjustments. 
     
     
         16 . The control system of  claim 9 , wherein the controller adjusts one or more of an elevation at one or more endpoints of the primitives, a location of one or more of the endpoints, and a number of the endpoints. 
     
     
         17 . (canceled) 
     
     
         18 . (canceled) 
     
     
         19 . (canceled) 
     
     
         20 . (canceled)