Inertial Safety from Structured Light

ECCV 2020  ·  Sizhuo Ma, Mohit Gupta ·

We present inertial safety maps (ISM), a novel scene representation designed for fast detection of obstacles in scenarios involving camera or scene motion, such as robot navigation and human-robot interaction. ISM is a motion-centric representation that encodes both scene geometry and motion; different camera motion results in different ISMs for the same scene. We show that ISM can be estimated with a two-camera stereo setup without explicitly recovering scene depths, by measuring differential changes in disparity over time. We develop an active, single-shot structured light-based approach for robustly measuring ISM in challenging scenarios with textureless objects and complex geometries. The proposed approach is computationally light-weight, and can detect intricate obstacles (e.g., thin wire fences) by processing high-resolution images at high-speeds with limited computational resources. ISM can be readily integrated with depth and range maps as a complementary scene representation, potentially enabling high-speed navigation and robotic manipulation in extreme environments, with minimal device complexity.

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