Patent ID: 11892297
Assignee: ROBERT BOSCH GMBH
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method of solving a graph simultaneous localization and mapping (graph SLAM) problem for HD maps using a distributed computing system, the method comprising:
partitioning a graph into a plurality of subgraphs using at least one processor of the distributed computing system, the graph including a plurality of vertices and a plurality of edges that extend between vertices, each of the vertices corresponding to a pose during mapping, each of the edges defining a spatial constraint between two vertices, wherein each of the subgraphs includes all of the vertices of the graphs, and wherein each of the subgraphs include a subset of the edges of the graph;
defining constrained, non-constrained and native vertices for each of the subgraphs using the at least one processor;
defining an alternating direction method of multipliers (ADMM) formulation for Graph SLAM based on the partitioned graph using the at least one processor;
defining updates for the ADMM formulation based on the ADMM algorithm using the at least one processor;
defining updates for a distributed Graph SLAM algorithm based on the updates for the ADMM formulation and in terms of the constrained and the non-constrained vertices of the subgraphs using the at least one processor; and
solving the updates for the distributed Graph SLAM algorithm to solve the Graph SLAM problem for HD maps using the at least one processor to provide a distributed computing solution for the Graph SLAM problem for HD maps,
wherein the ADMM formulation is a consensus ADMM formulation given by, arg
       ⁢
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       Δ
       ⁢
       
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  ,
  

  
   
    subject
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   =
   
    
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wherein k is a number of iterations,
wherein s is a number of graph nodes,
wherein T is a number of the poses,
wherein Δxk∈dN denotes an updated pose,
wherein bk∈dN denotes a gradient of cost functional error, and
wherein Hsk is a Hessian matrix of the cost functional error.