ROCVLGJun 14, 2023

3-Dimensional Sonic Phase-invariant Echo Localization

arXiv:2306.08281v23 citationsh-index: 9
Originality Highly original
AI Analysis

This addresses robotic vision challenges in varied conditions like light and weather, offering a novel acoustic-based alternative to camera systems.

The paper tackles 3D object localization using acoustic Time-of-Flight by introducing Parallax among Corresponding Echoes (PaCE), a method that triangulates echoes from arbitrary sensor positions to achieve phase-invariant localization with relaxed constraints.

Parallax and Time-of-Flight (ToF) are often regarded as complementary in robotic vision where various light and weather conditions remain challenges for advanced camera-based 3-Dimensional (3-D) reconstruction. To this end, this paper establishes Parallax among Corresponding Echoes (PaCE) to triangulate acoustic ToF pulses from arbitrary sensor positions in 3-D space for the first time. This is achieved through a novel round-trip reflection model that pinpoints targets at the intersection of ellipsoids, which are spanned by sensor locations and detected arrival times. Inter-channel echo association becomes a crucial prerequisite for target detection and is learned from feature similarity obtained by a stack of Siamese Multi-Layer Perceptrons (MLPs). The PaCE algorithm enables phase-invariant 3-D object localization from only 1 isotropic emitter and at least 3 ToF receivers with relaxed sensor position constraints. Experiments are conducted with airborne ultrasound sensor hardware and back this hypothesis with quantitative results.

Code Implementations1 repo
Foundations

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