The Dilemma of Decision-Making in the Real World: When Robots Struggle to Make Choices Due to Situational Constraints

TL;DR

This paper analyzes the decision-making challenges faced by assistive robots in noisy, uncertain real-world environments, proposing a scenario analysis approach to improve human-robot collaboration and personalization.

Contribution

It introduces a novel scenario analysis method to evaluate and address decision-making limitations of robots in complex, real-world settings, emphasizing user-centered design.

Findings

Highlights decision-making challenges in noisy environments

Proposes scenario analysis to improve robot personalization

Aims to enhance human-robot collaboration strategies

Abstract

In order to demonstrate the limitations of assistive robotic capabilities in noisy real-world environments, we propose a Decision-Making Scenario analysis approach that examines the challenges due to user and environmental uncertainty, and incorporates these into user studies. The scenarios highlight how personalization can be achieved through more human-robot collaboration, particularly in relation to individuals with visual, physical, cognitive, auditory impairments, clinical needs, environmental factors (noise, light levels, clutter), and daily living activities. Our goal is for this contribution to prompt reflection and aid in the design of improved robots (embodiment, sensors, actuation, cognition) and their behavior, and we aim to introduces a groundbreaking strategy to enhance human-robot collaboration, addressing the complexities of decision-making under uncertainty through a Scenario analysis approach. By emphasizing user-centered design principles and offering actionable solutions to real-world challenges, this work aims to identify key decision-making challenges and propose potential solutions.