Behavior-Based SSVEP Hierarchical Architecture for Telepresence Control of Humanoid Robot to Achieve Full-Body Movement

摘要

The challenge to telepresence control a humanoid robot through a steady-state visual evoked potential (SSVEP) based model is to rapidly and accurately control full-body movement of the robot because a subject has to synchronously recognize the complex natural environments based on live video feedback and activate the proper mental states by targeting the visual stimuli. To mitigate this problem, this paper presents a behavior-based hierarchical architecture, which coordinates a large number of robot behaviors using only the most effective five stimuli. We defined and implemented fourteen robot behaviors for motion control and object manipulation, which were encoded through the visual stimuli of SSVEPs, and classified them into four behavioral sets. We proposed switch mechanisms in the hierarchical architecture to coordinate these behaviors and control the full-body movement of a NAO humanoid robot. To improve operation performance, we investigated the individual sensitivities of visual stimuli and allocated the stimuli targets according to frequency-responsive properties of individual subjects. We compared different types of walking strategies. The experimental results showed that the behavior-based SSVEP hierarchical architecture enabled the humanoid robot to complete an operation task, including navigating to an object and picking the object up with a fast operation time and a low chance of collision in an environment cluttered with obstacles.