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<p>Autonomous robots are deployed in real-world applications, where reliable localization is a key enabler of safe autonomy. This paper extends Basalt, a stereo Visual-Inertial Odometry (VIO) system, to support multi-camera rigs on embedded edge devices, improving accuracy and robustness in low-texture and dynamic environments. We introduce a multi-camera VIO formulation that leverages Basalt’s sliding-window bundle adjustment to fuse measurements from additional cameras. In addition, we design a TBB-parallelized multi-camera front-end that performs image-pyramid construction and frame-to-frame feature tracking concurrently across synchronized image streams. Overlapping fields of view across cameras improve cross-view consistency and provide stable metric initialization. We evaluate three-, four-, and six-camera configurations on a quadcopter equipped with an NVIDIA Jetson Orin NX in indoor and outdoor scenarios, using motion capture as ground truth for indoor flights. The proposed system achieves end-to-end latency below 30 ms while reducing drift and attaining lower estimation errors than existing methods in most scenarios.</p>

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Scalable Multi-Camera VIO with Bounded Sliding-Window Optimization

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月28日

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  • Simone Godio,
  • Rafael Costa Fernandes,
  • Reem Ashour,
  • Adrian Bojko,
  • Chao Yao,
  • Claudio Tortorici

摘要

Autonomous robots are deployed in real-world applications, where reliable localization is a key enabler of safe autonomy. This paper extends Basalt, a stereo Visual-Inertial Odometry (VIO) system, to support multi-camera rigs on embedded edge devices, improving accuracy and robustness in low-texture and dynamic environments. We introduce a multi-camera VIO formulation that leverages Basalt’s sliding-window bundle adjustment to fuse measurements from additional cameras. In addition, we design a TBB-parallelized multi-camera front-end that performs image-pyramid construction and frame-to-frame feature tracking concurrently across synchronized image streams. Overlapping fields of view across cameras improve cross-view consistency and provide stable metric initialization. We evaluate three-, four-, and six-camera configurations on a quadcopter equipped with an NVIDIA Jetson Orin NX in indoor and outdoor scenarios, using motion capture as ground truth for indoor flights. The proposed system achieves end-to-end latency below 30 ms while reducing drift and attaining lower estimation errors than existing methods in most scenarios.