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

Abstract

Abstract-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.Index Terms-Brain-robot interaction (BRI), electroencephalogram (EEG), full-body movement, humanoid robot, steady-state visual evoked potential (SSVEP), telepresence control.

Online Covariate Shift Detection-Based Adaptive Brain–Computer Interface to Trigger Hand Exoskeleton Feedback for Neuro-Rehabilitation

“…µ= [8][9][10][11][12] Hz, β= [16][17][18][19][20][21][22][23][24] Hz). These two frequency ranges have been chosen empirically as they provide stable frequency response for Event-Related-Desynchronization or Event-Related-Synchronization (ERD/ERS) [43].…”

“…The strong correlation between EEG signals and mental tasks has led to many user centric applications such as virtual spellers for the communication [7], functional electrical stimulation (FES) based neuro-prosthesis for tetraplegics [4], hand exoskeleton control [8], [9], [10], [11] and telepresence for personal assistance [12]. In spite of the seemingly bright prospect of the BCI technology, there are some practical challenges regarding the robustness, accuracy, and information transfer rate (ITR) of such systems [13], [14], [15].…”

Towards a Robust Software Architecture for Autonomous Robot Software

“…Such architectures emphasis on a tight coupling between sensing and action, and decomposition into behavioral units [15], [22]. [24], [25] proposes a behavior-based SSVEP hierarchical architecture, consisting of an SSVEP model layer, a behavior mapping layer, and a humanoid controller layer. A bio-inspired, incremental, behavior-based architecture is proposed by Fabian [8], which is composed of two layers by using instinctive or deliberative reactions.…”

Accompanying Observation Modes and Software Architecture for Autonomous Robot Software

“…In the field of the behavior of autonomous robots, there are many researches focus on behavior-based model for robot [3]- [5]. And in recent year, [6] presented a behavior-based hierarchical architecture and defined fourteen robot behaviors to assist telepresence control a humanoid robot. [7] reproduced the kind of individual recognition and attention that a human can provide in robot based on observed behavior.…”