Reliability-Adaptive Multimodal Relative Pose Tracking for Underwater Leader-Follower Robots
- Published
- Source
- arXiv
- Paper number
- 1429
- Field
- Robotics
- arXiv ID
- 2611.11940
Key points
- The authors propose a reliability-adaptive multimodal perception framework for six-degree-of-freedom relative-pose tracking between two moving underwater robots.
- They explain that light absorption, scattering, color distortion, and suspended particulates severely reduce the reliability of optical measurements.
- They collected 12 trials for each combination of two leader types, three illumination conditions, and nine trajectory patterns, yielding 648 trials in total.
- In pool experiments, the framework achieves a mean translational error of 3.8 cm.
- On an onboard NVIDIA Jetson AGX Orin, the fusion network achieves an inference latency of 17.62 ms.
- A multimodal dataset containing measurements from all 648 trials will be made publicly available.
Paper links
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