Nvidia Corporation

California Institute of Technology

Guanya Shi

Jonathan Tremblay

Fabio Tozeto Ramos

Anima Anandkumar

Yuke Zhu

Soon-Jo Chung

Yisong Yue

Animashree Anandkumar

Xichen Shi

Michael O'Connell

Apparatuses, systems, and techniques generate poses of an object based on image data of the object obtained from a first viewpoint of the object and a second viewpoint of the object. The poses can be evaluated to determine a portion of the image data usable by an estimator to generate a pose of the object.

Data selection based on uncertainty quantification

Apparatuses, systems, and techniques generate poses of an object based on data of the object observed from a first viewpoint and a second viewpoint. The poses can be evaluated to determine a portion of the data usable by an estimator to generate a pose of the object.

Systems and methods for learning based control in accordance with embodiments of the invention are illustrated. One embodiment includes a method for training an adaptive controller. The method includes steps for receiving a set of training data that includes several training samples, wherein each training sample includes a state and a true uncertain effect value. The method includes steps for computing an uncertain effect value based on the state, computing a set of one or more losses based on the true uncertain effect value and the computed uncertain effect value, and updating the adaptive controller based on the computed set of losses.

Systems and methods for robust learning-based control during forward and landing flight under uncertain conditions

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Pasadena, CA, United States of America

Guanya Shi