US 12,000,965 B2 · Creating multi-return map data from single return lidar data

Abstract

System and methods for creating multi-return map data using single return Lidar data. The systems and methods use a long short-term memory (LSTM) model in combination with a Generative Adversarial Network (GAN) model. The systems and method use a single (1st) return of Lidar at a time stamp and create multiple unseen samples of 2nd and 3rd returns. The LSTM model is used to create a sequential calibration based on incidence angle to choose the optimized 2nd and 3rd return at the same instance of the time stamp. This creates a localized model of three returns from a single return of Lidar and thus provides additional data to generate an HD map.

Claims20

Dependent claims

A system comprising:

a memory configured to store single return Lidar data and real multi-return Lidar data;
a generative network configured to input the single return Lidar data and generate synthetic multi-return Lidar data;
and
a discriminator network configured to distinguish the synthetic multi-return Lidar data from the real multi-return Lidar data;
wherein the generative network and discriminator network are iteratively trained using an adversarial approach where the generative network learns to generate more plausible synthetic multi-return Lidar data, while the discriminative network attempts to distinguish synthetic multi-return Lidar data produced by the generative network from the real multi-return Lidar data.

2 more elements

Dependencies are inferred from the claim text.

Creating multi-return map data from single return lidar data

Life of this patent

Creating multi-return map data from single return lidar data

Life of this patent

Abstract

Claims20