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A Novel Multi-Sensor Nonlinear Tightly-Coupled Framework for Composite Robot Localization and Mapping.

Lu Chen1,2, Amir Hussain1,2, Yu Liu1

  • 1School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China.

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Summary

This study introduces a new sensor fusion framework, IIVL-LM, for improved robot localization and navigation in challenging conditions. The system enhances accuracy and reliability, especially in low-light environments, by integrating multiple sensors.

Keywords:
SLAMcomposite robotsilluminance conversionmulti-sensor fusionnonlinear tight coupling

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Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Composite robots face challenges in perception and pose estimation due to illumination changes, disturbances, and sensor errors.
  • Existing systems struggle with accuracy and reliability in dynamic and low-light environments.

Purpose of the Study:

  • To develop an integrated localization and navigation framework, IIVL-LM, that overcomes environmental perception and pose estimation difficulties.
  • To enhance the robustness and precision of robot systems in complex, variable conditions.

Main Methods:

  • Proposed a nonlinear optimization approach for tightly coupled data-level fusion of IMU, infrared, RGB camera, and LiDAR data.
  • Developed a real-time luminance calculation model and a fast approximation method for feature fusion.
  • Optimized the Visual-Inertial Odometry (VIO) module using infrared camera depth information within the R3LIVE++ framework.

Main Results:

  • The IIVL-LM system demonstrated significant performance improvements in challenging luminance conditions, particularly in low-light environments.
  • Achieved an average RMSE ATE improvement of 23% to 39% (0.006 to 0.013) in simulated indoor rescue scenarios.
  • Verified the critical importance of infrared image fusion through comparative experiments on the TUM-VI dataset.

Conclusions:

  • The IIVL-LM framework significantly boosts robot robustness and precision in unknown and expansive environments by maintaining active engagement of at least three sensors.
  • This integrated approach is crucial for applications requiring high reliability in complex scenarios, such as indoor rescue operations.