Uatc, LLC

Aurora Operations, Inc.

Xinchen Yan

Raquel Urtasun

Shenlong Wang

Sivabalan Manivasagam

Ersin Yumer

Shivam Duggal

Yun Chen

Frieda Rong

Justin Liang

Adam Wlodzimierz Harley

Mehmet Ersin Yumer

Ricson Cheng

Systems and methods for generating simulation data based on real-world environments are provided. A method includes obtaining multi-modal sensor data indicative of a dynamic object within an environment of a robotic platform. The multi-modal sensor data is associated with a plurality of timesteps including a first timestep and a second timestep. The method includes providing the multi-modal sensor data indicative of the dynamic object within the environment as an input to a machine-learned dynamic object removal model. And, the method includes receiving as an output of the machine-learned dynamic object removal model, in response to receipt of the multi-modal sensor data, a scene representation indicative of at least a portion of the environment including a reconstructed region based at least in part on removal of the dynamic object and multiple levels of granularity. The scene representation is used as a template for generating different simulations within the depicted environment.

Systems and methods for dynamic object removal from three-dimensional data

The present disclosure provides systems and methods for generating photorealistic image simulation data with geometry-aware composition for testing autonomous vehicles. In particular, aspects of the present disclosure can involve the intake of data on an environment and output of augmented data on the environment with the photorealistic addition of an object. As one example, data on the driving experiences of a self-driving vehicle can be augmented to add another vehicle into the collected environment data. The augmented data may then be used to test safety features of software for a self-driving vehicle.

Photorealistic image simulation with geometry-aware composition

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San Mateo, CA, United States of America

Xinchen Yan