Object SLAM With Robust Quadric Initialization and Mapping for Dynamic Outdoors

Rui Tian, Yunzhou Zhang, Zhenzhong Cao, Jinpeng Zhang, Linghao Yang, Sonya Coleman, Dermot Kerr, Kun Li

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Object SLAM is a popular approach for autonomous driving and robotics, but accurate object perception in outdoor environments remains a challenge. State-of-the-art object SLAM algorithms rely on assumptions and are sensitive to observation noise, limiting their application in real-world scenarios. To address these challenges, we propose a novel object SLAM system that utilizes a quadric initialization algorithm based on constrained quadric optimization, which does not rely on planar assumptions and is robust to partial observations. Additionally, we introduce an automatic object data association algorithm capable of detecting motion states while associating objects across frames. To further enhance the accuracy of the quadric mapping, an extra thread is used to refine the ellipsoid parameters within a local sliding window composed of keyframes. Our system utilizes a joint optimization framework that optimizes camera poses, object landmarks, and point clouds in the local mapping thread for further global optimization while maintaining a consistent map. Experimental results on the real-world KITTI dataset show that the proposed system is more robust and significantly outperforms current state-of-the-art methods in quadric initialization and mapping in outdoor scenarios. Moreover, our system achieves real-time performance, making it suitable for practical applications.
Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalIEEE Transactions on Intelligent Transportation Systems
Publication statusPublished (in print/issue) - 12 Jun 2023

Bibliographical note

Publisher Copyright:


  • Simultaneous localization and mapping
  • Heuristic algorithms
  • Ellipsoids
  • Cameras
  • Solid modeling
  • Optimization
  • Instruction sets
  • quadric mapping
  • data association
  • object SLAM
  • Robotics
  • visual localization


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