Human-in-the-loop testing of the explainability of robot navigation algorithms in extended reality

Developing robots to be deployed in spaces shared with people requires testing with humans-in-the-loop. In fact, only humans co-located with the robots are in a suitable position to judge the robots’ behaviors. This is especially important when people participate in the same task as the robots, like when navigating a shared environment: the actions of people and robots influence each other. To test the resulting dynamic system, we need to let real people experience the interaction, which, when done in simulation, translates to immersing real users using Virtual or Mixed Reality. We implement and demonstrate this solution where users experience variable legibility, predictability, and explainability of the robot navigation algorithms, depending on if and how the robots explicitly communicate their intentions.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-21
DOI
https://doi.org/10.5281/zenodo.14864852
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Human-in-the-loop testing of the explainability of robot navigation algorithms in extended reality

Zenodo (CERN European Organization for Nuclear Research)
Social Robot Interaction and HRI
article

Human-in-the-loop testing of the explainability of robot navigation algorithms in extended reality

article en

Abstract

Developing robots to be deployed in spaces shared with people requires testing with humans-in-the-loop. In fact, only humans co-located with the robots are in a suitable position to judge the robots’ behaviors. This is especially important when people participate in the same task as the robots, like when navigating a shared environment: the actions of people and robots influence each other. To test the resulting dynamic system, we need to let real people experience the interaction, which, when done in simulation, translates to immersing real users using Virtual or Mixed Reality. We implement and demonstrate this solution where users experience variable legibility, predictability, and explainability of the robot navigation algorithms, depending on if and how the robots explicitly communicate their intentions.

Zenodo (CERN European Organization for Nuclear Research)
Dalle Molle Institute for Artificial Intelligence Research (CH)
Openalex Percentile: Top 46%
Social Robot Interaction and HRI
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.