AICVHCLGROJul 20, 2017

Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills

arXiv:1707.06633v422 citations
Originality Highly original
AI Analysis

This addresses the need for user-friendly robotic interfaces for paralyzed users who cannot use traditional touch, speech, or gesture controls, representing a novel application rather than an incremental improvement.

The paper tackles the problem of enabling paralyzed users to control a robotic service assistant using only thoughts, via a non-invasive brain-computer interface (BCI) system, and demonstrates its applicability and robustness in real-world fetch-and-carry and human-robot interaction tasks, completing tasks reliably within a reasonable time.

As autonomous service robots become more affordable and thus available also for the general public, there is a growing need for user friendly interfaces to control the robotic system. Currently available control modalities typically expect users to be able to express their desire through either touch, speech or gesture commands. While this requirement is fulfilled for the majority of users, paralyzed users may not be able to use such systems. In this paper, we present a novel framework, that allows these users to interact with a robotic service assistant in a closed-loop fashion, using only thoughts. The brain-computer interface (BCI) system is composed of several interacting components, i.e., non-invasive neuronal signal recording and decoding, high-level task planning, motion and manipulation planning as well as environment perception. In various experiments, we demonstrate its applicability and robustness in real world scenarios, considering fetch-and-carry tasks and tasks involving human-robot interaction. As our results demonstrate, our system is capable of adapting to frequent changes in the environment and reliably completing given tasks within a reasonable amount of time. Combined with high-level planning and autonomous robotic systems, interesting new perspectives open up for non-invasive BCI-based human-robot interactions.

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