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OTE-SLAM: An Object Tracking Enhanced Visual SLAM System for Dynamic Environments.

Yimeng Chang1, Jun Hu1, Shiyou Xu1

  • 1School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, China.

Sensors (Basel, Switzerland)
|September 28, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces OTE-SLAM, an object tracking enhanced visual Simultaneous Localization and Mapping (SLAM) system. It improves camera pose accuracy in dynamic environments by jointly optimizing camera and object movement.

Keywords:
dynamic environmentsobject trackingvisual SLAM

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Area of Science:

  • Robotics
  • Computer Vision
  • Autonomous Systems

Background:

  • Visual Simultaneous Localization and Mapping (SLAM) is crucial for autonomous systems.
  • Traditional SLAM systems assume scene rigidity, failing in dynamic environments.
  • Excluding dynamic features can lead to insufficient tracking data.

Purpose of the Study:

  • To develop an object tracking enhanced visual SLAM system (OTE-SLAM).
  • To address the limitations of rigid-scene assumptions in dynamic environments.
  • To improve camera pose estimation accuracy in challenging scenarios.

Main Methods:

  • Proposed OTE-SLAM integrates object tracking with visual SLAM.
  • Joint optimization of camera pose and dynamic object 3D positions.
  • Leverages mutual benefits between SLAM and object tracking.

Main Results:

  • Demonstrated improved accuracy of the SLAM system in dynamic environments.
  • Achieved a maximum reduction of 22% in Absolute Trajectory Error (ATE).
  • Achieved a maximum reduction of 33% in Relative Trajectory Error (RTE).

Conclusions:

  • OTE-SLAM effectively handles dynamic objects in visual SLAM.
  • Joint optimization enhances robustness and accuracy in challenging environments.
  • The approach offers significant improvements for autonomous applications.