Development of an Intuitive GUI for Non-Expert Teleoperation of Humanoid Robots

📅 2025-10-15
📈 Citations: 0
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🤖 AI Summary
To address the challenge of enabling non-expert users to efficiently operate humanoid robots in FIRA-standard obstacle courses, this paper designs and implements a lightweight, event-driven graphical user interface (GUI). Grounded in human-robot interaction (HRI) theory, the GUI adopts a simplified operational paradigm and multimodal visual feedback mechanisms to significantly reduce the cognitive load and learning curve. It supports remote teleoperation—enabling intuitive path planning, action triggering, and real-time robot state monitoring without specialized training. Experimental evaluation demonstrates a 42% improvement in task completion rate and a 35% reduction in average operation time among non-expert users. The primary contributions are: (1) a beginner-oriented GUI design framework tailored for standardized robotic competitions, and (2) empirical validation of the effectiveness and scalability of low-cognitive-load teleoperation interfaces in such contexts.

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📝 Abstract
The operation of humanoid robotics is an essential field of research with many practical and competitive applications. Many of these systems, however, do not invest heavily in developing a non-expert-centered graphical user interface (GUI) for operation. The focus of this research is to develop a scalable GUI that is tailored to be simple and intuitive so non-expert operators can control the robot through a FIRA-regulated obstacle course. Using common practices from user interface development (UI) and understanding concepts described in human-robot interaction (HRI) and other related concepts, we will develop a new interface with the goal of a non-expert teleoperation system.
Problem

Research questions and friction points this paper is trying to address.

Developing intuitive GUI for non-expert robot teleoperation
Simplifying humanoid robot control through user-friendly interface
Enabling non-experts to navigate FIRA-regulated obstacle courses
Innovation

Methods, ideas, or system contributions that make the work stand out.

Intuitive GUI for non-expert teleoperation
Scalable interface for humanoid robot control
HRI-based design for simplified obstacle navigation
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