Visual perception system and method for a humanoid robot

A robotic system includes a humanoid robot with robotic joints each moveable using an actuator(s), and a distributed controller for controlling the movement of each of the robotic joints. The controller includes a visual perception module (VPM) for visually identifying and tracking an object in the field of view of the robot under threshold lighting conditions. The VPM includes optical devices for collecting an image of the object, a positional extraction device, and a host machine having an algorithm for processing the image and positional information. The algorithm visually identifies and tracks the object, and automatically adapts an exposure time of the optical devices to prevent feature data loss of the image under the threshold lighting conditions. A method of identifying and tracking the object includes collecting the image, extracting positional information of the object, and automatically adapting the exposure time to thereby prevent feature data loss of the image

A model of proactive and reactive cognitive control with anterior cingulate cortex and the neuromodulatory system

Abstract Proactive and reactive cognitive control are often associated with anterior cingulate cortex (ACC). How ACC affects processing in other brain areas, however, is often not explicitly delineated. In this work, we describe a model of how ACC computes measures of conflict and surprise that are in turn relayed to the basal forebrain (BF) and locus coeruleus (LC) in that order. BF and LC signals then respectively sharpen posterior cortical processing and trigger the reframing of prefrontal cortical decision-making frames. We implemented this theory in a large-scale neurocognitive model that performs simulated geospatial intelligence tasks. Experiments demonstrate improved performance while minimizing additional processing. Alternate interpretations of neuromodulatory signals are also discussed.