Presentation
Inspection Robot Path and Manual Takeover Modality Influence Human Takeover Decisions
DescriptionExterior visual inspection of the International Space Station (ISS) is essential for safety, but presents significant risks to astronauts. This study evaluated how robot path-planning constraints and manual takeover modalities influence anomaly detection performance (ADP) in human-robot teams. Using a simulated ISS environment, 40 participants performed inspections under varying conditions, comparing paths with and without a local constraint (sequential module-by-module inspection) and availability of a rotation-only manual takeover. Findings reveal that the local constraint significantly improved ADP. Anomaly detectability was significantly affected by anomaly placement as station geometry could limit camera angles supporting anomaly observability. The results demonstrate that optimizing robotic trajectories for fuel and coverage is insufficient; integrating human-aware constraints into path generation is critical for enhancing operator situation awareness and overall mission success in complex orbital environments.
Event Type
Lecture
TimeThursday, October 22nd3:20pm - 3:40pm PDT
Location