arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1809.06977cs.RO

An Orientation Factor for Object-Oriented SLAM

ARC Centre of Excellence for Robotic Vision(澳大利亚研究理事会机器人视觉卓越中心);Queensland University of Technology(昆士兰科技大学)

Natalie Jablonsky, Michael Milford, Niko Sünderhauf

英文摘要:

Current approaches to object-oriented SLAM lack the ability to incorporate prior knowledge of the scene geometry, such as the expected global orientation of objects. We overcome this limitation by proposing a geometric factor that constrains the global orientation of objects in the map, depending on the objects' semantics. This new geometric factor is a first example of how semantics can inform and improve geometry in object-oriented SLAM. We implement the geometric factor for the recently proposed QuadricSLAM that represents landmarks as dual quadrics. The factor probabilistically models the quadrics' major axes to be either perpendicular to or aligned with the direction of gravity, depending on their semantic class. Our experiments on simulated and real-world datasets show that using the proposed factors to incorporate prior knowledge improves both the trajectory and landmark quality.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑