Design-time improvement using a functional approach to specify GraphSLAM with deterministic performance on an FPGA

Abstract

SLAM is a fundamental problem in robotics that can be solved by a set of algorithms that are known to have large computational complexity. GraphSLAM contains a rapidly growing system of equations which are often solved by sparse evaluation techniques. This paper proposes a technique to evaluate sparse equations on an FPGA by restricting the maximum amount of items in the system. The implementation is done using CλaSH which allows a transformation from mathematical descriptions to a hardware design. The results show a scalable hardware design that can be used to solve small and large systems with dynamic parallelism.