Control Without Control: Defining Implicit Interaction Paradigms for Autonomous Assistive Robots

TL;DR

This paper explores implicit control in assistive robots, where behavior adapts to users' cues, enhancing perceived control and reducing workload, with guidelines for designers.

Contribution

It introduces a new interaction paradigm called implicit control, demonstrated through two case studies, with insights on user perception and design guidelines.

Findings

Implicit control reduces perceived workload.

Designs that are intuitive and responsive preserve user control.

Contextual awareness and adaptability are key for effective implicit interaction.

Abstract

Assistive robotic systems have shown growing potential to improve the quality of life of those with disabilities. As researchers explore the automation of various caregiving tasks, considerations for how the technology can still preserve the user's sense of control become paramount to ensuring that robotic systems are aligned with fundamental user needs and motivations. In this work, we present two previously developed systems as design cases through which to explore an interaction paradigm that we call implicit control, where the behavior of an autonomous robot is modified based on users' natural behavioral cues, instead of some direct input. Our selected design cases, unlike systems in past work, specifically probe users' perception of the interaction. We find, from a new thematic analysis of qualitative feedback on both cases, that designing for effective implicit control enables both a reduction in perceived workload and the preservation of the users' sense of control through the system's intuitiveness and responsiveness, contextual awareness, and ability to adapt to preferences. We further derive a set of core guidelines for designers in deciding when and how to apply implicit interaction paradigms for their assistive applications.