Updating egocentric representations in human navigation widows dating children

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We are currently further developing novel methods to measure the time course of mind wandering, as well as the neural signature of these spontaneous cognitive processes.

It has been a great challenge to design a robot that can drive by itself to a goal without bumping into obstacles on the way.

It is well known that memories can become distorted by people’s concepts and schemas.

Cristina Sampaio and I examined one of the long-debated questions about memory distortions, i.e., whether memory representations are distorted, or the memories themselves are intact but errors occur when multiple representations are combined to make a response.

Because the egocentric coordinates of each target need to be “calculated” individually, the number of target locations one can update should be limited by the processing capacity.

That is, the efficiency of spatial updating should depend on the number of targets being updated, while traditional and intuitive models of spatial updating (e.g., mentally “plotting” one’s position on a “map” as one moves around) predict that the number of targets in the environment should not matter.

Quadrotor flight paths were manipulated in terms of velocity, altitude, and acoustic profile to examine their effect on physiological arousal and head motion kinematics.

For all three experiments, arousal was greater when the quadrotor was flying at higher speed, with the audio on, and at eye-height than overhead, but decreased across subsequent trials.

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In one approach, we used a recognition task to see whether an unbiased memory representation can be accessed.As expected, humans showed significantly more robust performance compared to that of a receding horizon controller.Using the human data, we then trained a new human-like receding horizon controller which achieved better performance in the percentage of successful run to the goal without collision with the obstacles and the time required to reach the goal.This control problem has engaged much research, however consistent performance is still not available, especially in cluttered environments and with concave obstacles.

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In contrast, humans and many animals can maneuver with much more dexterity, but how they achieve this performance is poorly understood at the mathematical level.

Moreover, these representations are updated independently based on the observer’s estimation of self motion, and thus vulnerable to disorientation.

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