US Patent Issued to Zoox on Feb. 24 for "Machine-learned model architecture for diverse object path prediction" (California Inventors)

ALEXANDRIA, Va., Feb. 24 -- United States Patent no. 12,559,138, issued on Feb. 24, was assigned to Zoox Inc. (Foster City, Calif.).

"Machine-learned model architecture for diverse object path prediction" was invented by Gregory Michael Woelki (Foster City, Calif.), Xiaosi Zeng (Redwood City, Calif.), Gowtham Garimella (Hayward, Calif.), Samir Parikh (Los Gatos, Calif.) and Ethan Miller Pronovost (Redwood City, Calif.).

According to the abstract* released by the U.S. Patent & Trademark Office: "A machine-learned architecture may predict a set of spatially-diverse paths that an object may take in the future. The paths generated by this architecture may be time-invariant (e.g., not identifying a time at which the object may occupy a positio...