360ST-Mapping: An Online Semantics-Guided Topological Mapping Module for Omnidirectional Visual SLAM

Hongji Liu, Huajian Huang, Sai-Kit Yeung, Ming Liu

Abstract: As an abstract representation of the environment structure, a topological map has advantageous properties for path-planning and navigation. Here we proposed an online topological mapping method, 360ST-Mapping, using omnidirectional vision. The 360° field-of-view allows the agent to obtain consistent observation and incrementally extract topological environment information. Moreover, we leverage semantic infor-mation to guide topological place recognition, further improving performance. The topological map possessing semantic infor-mation has the potential to support semantics-related advanced tasks. After integrating the topological mapping module into the omnidirectional visual SLAM system, we conducted extensive experiments in several large-scale indoor scenes and validated the method's effectiveness.