An artificial life environment for autonomous virtual agents with multi‐sensorial and multi‐perceptive features

Abstract

Our approach is based on the multi-sensory integration of the standard theory of neuroscience, where signals of a single object coming from distinct sensory systems are combined. The acquisition steps of signals, filtering, selection and simplification intervening before proprioception, active and predictive perception are integrated into virtual sensors and a virtual environment. We will focus on two aspects: 1) the assignment problem: determining which sensory stimuli belong to the same virtual object and (2) the sensory recoding problem: recoding signals in a common format before combining them. We have developed three novel methodologies to map the information coming from the virtual sensors of vision, audition and touch as well as that of the virtual environment in the form of a 'cognitive map'.

Synthetic vision‐based perceptual attention for augmented reality agents

“…Thus, there have been studies considering how to equip agents with synthetic vision, audition, and touch. [2][3][4] Based on perception, perceptual attention provides agents with a way to attend their environment. 5,6 Augmented reality (AR) that enables users to experience computer-generated content embedded in a real environment 7 ; AR-based agents can thus be visualized among physical objects in users' environment, and directly interact with users in real-time.…”

Multisensorial Active Perception for Indoor Environment Modeling

“…In particular, the behavior any artificial or biological system should follow to accomplish certain tasks (e.g., extraction, simplification and filtering), is strongly influenced by the data supplied by its sensors. This data is in turn dependent on the perception criteria associated with each sensorial input (Conde & Thalmann, 2004).…”

Learnable behavioural model for autonomous virtual agents

“…Previously, [5] have proposed new methodologies to carry out the mapping of all information coming from virtual sensors of vision, audition and touch as well as from the Virtual Environment (VE) in the form of a "cognitive map". The approach enables the partial re-mapping of cognitive and semantic information at a behavioural level.…”