Abstract

Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it’s also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.

Highlights

  • Modern urban development and expansion has increasingly shifted to underground infrastructures to relieve ground traffic loads

  • We developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig

  • Our parallel motion estimation and mapping system is capable of operating in underground environment with poor illumination and without GPS signal

Read more

Summary

INTRODUCTION

Modern urban development and expansion has increasingly shifted to underground infrastructures to relieve ground traffic loads. The predominant practice for 3D mapping of underground infrastructures is the use of tripod-mounted terrestrial laser scanners at a sequence of static stations (Fekte et al, 2010) This mapping method is accurate but consuming in both labour and instrument. (Robert et al, 2014) developed a solution capable of estimating the motion trajectory of mobile platforms as well as 3D point cloud of the environment. Their system is mainly depending on laser scanner as the primary sensor and has been installed in underground mines. While others (Peter Hansen et al, 2015) took the advantage of modern camera systems and established a visual mapping system for gas pipe inspection In their work, they used fisheye imaging to produce.

Parallel Structure
Motion Estimation
Mapping
Mobile 3D-Mapping System
Calibration and Rectification
Motion Estimation Results
CONCLUSIONS AND FUTURE WORKS
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call