This　paper　introduces　a　dedicated　processor　architecture,　called　MEGACORE,　which　leverages　vector　technology　to　enhance　tracking　performance　in　Visual　Simultaneous　Localization　and　Mapping　(VSLAM)　systems.　By　harnessing　the　inherent　parallelism　of　vector　processing　and　incorporating　a　floating　point　unit　(FPU),　MEGACORE　achieves　significant　acceleration　in　the　tracking　task　of　VSLAM.　Through　careful　optimizations,　we　achieved　notable　improvements　compared　to　the　baseline　design.　Our　optimizations　resulted　in　a　14.9%　reduction　in　the　area　parameter　and　a　4.4%　reduction　in　power　consumption.　Furthermore,　by　conducting　application　benchmarks,　we　determined　that　the　average　speedup　ratio　across　all　stages　of　the　tracking　process　is　3.25.　These　findings　highlight　the　effectiveness　of　MEGACORE　in　improving　the　efficiency　and　performance　of　VSLAM　systems,　making　it　a　promising　solution　for　real-world　implementations　in　embedded　systems.　IEEE