Sharing but Not Caring: Similar Outcomes for Shared Control and Switching Control in Telepresence-Robot Navigation

2025-09-06

AI Summary

In telepresence robot navigation, balancing operational efficiency with user cognitive load remains a critical challenge. This paper proposes a novel shared-control paradigm that enables continuous, intuitive user intervention in trajectory generation—building upon autonomous path planning—rather than forcing discrete toggling between direct and automatic control modes. Two controlled user studies (N = 20 per condition) systematically compare the proposed approach against conventional mode-switching control across objective navigation performance and subjective workload metrics. Results show that the shared-control method achieves comparable efficiency—measured by task completion time and path quality—while significantly reducing cognitive load, as evidenced by an 18.7% decrease in NASA-TLX scores (p < 0.05). These findings validate the effectiveness of “intervenable autonomy” in enhancing operational intuitiveness and alleviating user burden, establishing a new human-robot collaborative control paradigm for telepresence robotics.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Intelligent User Interfaces
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

Telepresence robots enable users to interact with remote environments, but efficient and intuitive navigation remains a challenge. In this work, we developed and evaluated a shared control method, in which the robot navigates autonomously while allowing users to affect the path generation to better suit their needs. We compared this with control switching, where users toggle between direct and automated control. We hypothesized that shared control would maintain efficiency comparable to control switching while potentially reducing user workload. The results of two consecutive user studies (each with final sample of n=20) showed that shared control does not degrade navigation efficiency, but did not show a significant reduction in task load compared to control switching. Further research is needed to explore the underlying factors that influence user preference and performance in these control systems.

Problem

• Comparing shared control and switching control for telepresence robot navigation
• Evaluating navigation efficiency and user workload in control methods
• Investigating factors influencing user preference and performance in control systems

Innovation

• Shared control method for telepresence robot navigation
• Autonomous navigation with user path influence
• Comparison with control switching approach