On Human Inspired Semantic SLAM's Feasibility

摘要

Robotic SLAM is attempting to learn robots what human beings do nearly effortlessly: to navigate in an unknown environment and to map it in the same time. In spite of huge advance in this area, nowadays SLAM solutions are not yet ready to enter the real world. In this paper, we observe the state of the art in existing SLAM techniques and identify semantic SLAM as one of prospective directions in robotic mapping research. We position our initial research into this field and propose a human inspired concept of SLAM based on understanding of the scene via its semantic analysis. First simulation results, using a virtual humanoid robot are presented to illustrate our approach.