Methods and apparatus for early sensory integration and robust acquisition of real world knowledge

A system for estimating at least one position of a robot moving through an environment, the system comprising:

• an interface to receive first sensor data from a first sensor and second sensor data from a second sensor, the first sensor data and the second sensor data representing measurements of the environment with respect to the robot;
• a memory, operably coupled to the interface, to store the first sensor data in a first neural representation of possible readings from the first sensor and to store the second sensor data in a second neural representation of possible readings from the second sensor;
• and
• a path integration module, operably coupled to the memory, to:
• (i) apply a first weight to the first sensor data in the first neural representation, the first weight representing a first measurement precision of the first sensor;
• (ii) apply a second weight to the second sensor data in the second neural representation, the second weight representing a first measurement precision of the first sensor;
• (iii) combine the first sensor data in the first neural representation with the second sensor data in the second neural representation so as to produce aggregated sensor data in an aggregated neural representation of the environment;
• and
• (iv) estimate a position of the robot with respect to the environment based at least in part on the aggregated neural representation of the environment.

A method of providing an estimate of at least one of a position of a robot and an orientation of the robot, the method comprising:

• (A) receiving a vestibular signal representative of the at least one of the orientation of the robot and the position of the robot;
• (B) receiving a motor outflow signal representative of commanded motion of the robot;
• (C) receiving an optical flow signal representative of the at least of the orientation of the robot and the position of the robot with respect to an environment of the robot;
• (D) weighting the vestibular signal received in (A), the motor outflow signal received in (B), and the optical flow signal received in (C) based on a type of the motion of the robot;
• (E) combining the vestibular signal, motor outflow signal, and optical flow signal weighted in (D) to produce a localization signal;
• and
• (F) generating, via at least one processor, the estimate of the at least one of the position of the robot and the orientation of the robot based on the localization signal produced in (E).