This patent's title says LiDAR but its classification says neural network. UATC's grant US11221413B2 ("Three-dimensional object detection," issued January 11, 2022; inventors Ming Liang, Bin Yang, Shenlong Wang, Wei-Chiu Ma, Raquel Urtasun) carries G06N 3/02, 3/04, and 3/08 — network architecture, layered structure, and training — right alongside the G01S LiDAR codes. The LiDAR is the input; the claimed invention is the network that turns points into boxes.
The mechanism is learned 3D detection: a neural network ingests LiDAR (G01S 17/89 imaging) and outputs 3D object detections, with G05D 1/0231 tying the result to vehicle position control. The inventor list is the giveaway — Urtasun's group produced foundational deep-LiDAR-detection work, and this claim fences that lineage at the point where point clouds become a learned detector's output.
For the control beat, what's striking is that this is one node in a deliberate multi-grant family: the same title and inventors recur across US11500099B2 (2022), US11768292B2 (2023), and US12051001B2 (2024). That cadence is a strategy, not an accident — a chain of continuations re-fencing 3D detection as the art moves, keeping a live, evolving claim set on the same core capability across four years.
From a portfolio angle, that continuation chain is the real asset, not any single grant. A reader auditing UATC's (and successor Aurora's) perception moat should read the family as a unit: each child can carry slightly different scope, and the latest live continuation defines what's actually enforceable today. A quiet continuation is a loud signal — here, of sustained investment in learned LiDAR detection.
Caveats. Deep 3D detection from LiDAR is among the most-published autonomy topics; any single claim faces heavy prior art, and granted scope hinges on the specific network or representation step in claim 1. The family's value is precisely that it spreads the bet across multiple claim formulations. Read the latest continuation's independent claim for current scope.
For the file: a foundational, multi-generation learned-LiDAR-detection family. Pull US11221413B2 and its 2022–2024 continuations on PatentBear, read the newest child's claim 1, and treat the chain — not the first grant — as the enforceable fence.