Honda Motor Co., Ltd.

Ran Tian

David Francis Isele

Masayoshi Tomizuka

Haiming Gang

Liting Sun

Systems and methods for incorporating latent states into robotic planning are provided. In one embodiment, the method includes identifying an agent team including at least one robotic agent and at least one human agent. The method also includes receiving sensor data associated with relative physical parameters between the at least one robotic agent and the at least one human agent. The method further includes modeling the latent states of the at least one human agent as a behavior model. The latent states describe cognition of the at least one human agent. The method includes calculating a first belief state based on the relative physical parameters and the behavior model. The method yet further includes predicting future probabilities of future observations at a second the future probabilities.

Systems and methods for incorporating latent states into robotic planning

Systems and methods for curiosity development in an agent located in an uncertain environment are provided. In one embodiment, the system includes a goal state module, a curiosity module, and a planning module. The goal module is configured to calculate a goal state of a goal associated with the environment. The curiosity module is configured to determine an uncertainty value for the environment and calculate a curiosity reward based on the uncertainty value. The planning module is configured to update a motion plan based on the goal state and the curiosity reward.

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Dublin, CA, United States of America

Ran Tian