Surface feature detection from point clouds for autonomous and semi-autonomous systems and applications

Abstract

In various examples, surface features such as lane lines or road boundaries may be detected and 2D or 3D polylines representing their shape may be regressed. For example, a set of predefined vertical, slanted, and/or curved anchors may be used to represent corresponding lines (e.g., in a top-down view or bird's eye view). For each anchor, extracted features may be sampled along the anchor and processed using one or more DNNs to generate global (e.g., anchor-level) predictions such as an anchor-level existence or confidence score and/or local (e.g., per-point) predictions for each of a set of sampled points along the anchor such as regressed polylines and per-point classifications. The detected surface features may be used by one or more control components such as a drive or control stack for localization, safe planning, and control of an autonomous vehicle, semi-autonomous vehicle, machine, robot, and/or other object or machine type.

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