PODER: A Robot Programming Framework to Further Inclusion of People with Mild Cognitive Impairment in HRI Research

Many HRI researchers have engaged in participatory research to include users in robot design processes. However, to our knowledge, people with mild cognitive impairment (PwMCI) and early stage dementia have yet to be included in developing and programming robots, and the HRI community lacks tools to facilitate their inclusion. We bridge this gap by introducing PODER (PrOgramming framework to Develop Robot behaviors), which enables a lived technology experience for PwMCI via scaffolding, peer programming, and development tools to support them as key developers of social robots. We conducted a study where PwMCI and early stage dementia used PODER to program robot interactions, and found that participants were highly engaged and deeply enjoyed their experience, creating programs for robots that reflected their interests, experiences, and needs. Our results show the impact of including participants with MCI and early stage dementia in robot programming, including an increased understanding of technology, shifting their perceived role from technology users to programmers, and desire to be involved with the end-to-end process. By releasing PODER to the community, we hope this work can facilitate the intentional inclusion of people with cognitive impairments in further HRI research.

Authors

Institutions

Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/hri61500.2025.10974039
Citations
3
Primary Topic
Cognitive Functions and Memory
Type
article
Field-Weighted Citation Impact
6.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PODER: A Robot Programming Framework to Further Inclusion of People with Mild Cognitive Impairment in HRI Research

Michele Murakami, Dagoberto Cruz‐Sandoval, Alyssa Kubota, Laurel D. Riek
3 citations
Cognitive Functions and Memory
6.35
article

PODER: A Robot Programming Framework to Further Inclusion of People with Mild Cognitive Impairment in HRI Research

Michele Murakami, Dagoberto Cruz‐Sandoval, Alyssa Kubota, Laurel D. Riek
article en
3 citations

Abstract

Many HRI researchers have engaged in participatory research to include users in robot design processes. However, to our knowledge, people with mild cognitive impairment (PwMCI) and early stage dementia have yet to be included in developing and programming robots, and the HRI community lacks tools to facilitate their inclusion. We bridge this gap by introducing PODER (PrOgramming framework to Develop Robot behaviors), which enables a lived technology experience for PwMCI via scaffolding, peer programming, and development tools to support them as key developers of social robots. We conducted a study where PwMCI and early stage dementia used PODER to program robot interactions, and found that participants were highly engaged and deeply enjoyed their experience, creating programs for robots that reflected their interests, experiences, and needs. Our results show the impact of including participants with MCI and early stage dementia in robot programming, including an increased understanding of technology, shifting their perceived role from technology users to programmers, and desire to be involved with the end-to-end process. By releasing PODER to the community, we hope this work can facilitate the intentional inclusion of people with cognitive impairments in further HRI research.

UC San Diego Health System (US), San Francisco State University (US)
National Science Foundation, University of California, San Diego
Reduced inequalities
Openalex Percentile: Top 4%
Cognitive Functions and Memory
6.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.