ArticleScientific reports2026
Delivery from the sky: investigating visual cues to communicate robot intentions in simulated public spaces.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Psychological uncertainty in human experience and behavior: a systematic review on measurements, induction, and effects.Frontiers in psychology · 2026Review
- Investigating social drones for recreational running through co-design.Frontiers in robotics and AI · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
As robots such as drones begin delivering packages from the sky in public spaces, humans will interact as recipients. Clear communication of a drone’s vertical motion and delivery intentions is essential to reduce feelings of uncertainty and build trust among the public. This study investigates how visual cues, including delivery methods and interfaces, communicate a drone’s drop-off and take-off intentions and affect recipients’ uncertainty in a simulated public environment. Through a video-based online questionnaire, 150 participants viewed scenarios where a drone delivered a package either by landing or via a cable-drop mechanism, each presented with or without visual interfaces such as onboard lights, a display, or ground projection. Participants rated the scenarios for uncertainty, understandability, predictability, trust, and convincingness, and provided qualitative feedback. Results show that visual interfaces improved participants’ ability to predict drone actions, increased certainty in approaching the drop-off spot, and improved trust. While lights posed challenges with visual clarity, both display and projection interfaces conveyed vertical motion and delivery intentions effectively. Projection was particularly recommended, as it marked the drop-off spot on the ground and a safety boundary. We discuss the implications of our findings beyond delivery scenarios, considering broader public space interactions with robots operating in vertical planes, and highlight the need for validation through real-world experiments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.