University of South Florida

Yongqiang Huang

Yu Sun

System and methods for generating a trajectory of a dynamical system are described herein. An example method includes modelling a policy from demonstration data. The method also includes generating a first set of action particles by sampling from the policy, where each of the action particles in the first set includes a respective system action, predicting a respective outcome of the dynamical system in response to each of the action particles in the first set, and weighting each of the action particles in the first set according to a respective probability of achieving a desired outcome. The method further includes generating a second set of action particles by sampling from the weighted action particles, where each of the action particles in the second set includes a respective system action, and selecting a next system action in the trajectory of the dynamical system from the action particles in the second set.

Systems and methods for learning and generating movement policies for a dynamical system

System and methods for generating a trajectory of a dynamical system are described herein. An example method can include generating a desired effect on the dynamical system in response to a plurality of system states and effects, where the desired effect is associated with a confidence value. The method can also include predicting a respective corresponding effect on the dynamical system in response to each of a plurality of possible system actions, where each respective corresponding effect is associated with a confidence value. The method can further include comparing each respective corresponding effect on the dynamical system to the desired effect on the dynamical system, and selecting a next system action in the trajectory of the dynamical system based on the comparison.

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Tampa, FL, United States of America

Yongqiang Huang