ArticleFrontiers in robotics and AI2025
Consideration of communication in human-machine interaction for cooperative trajectory planning.
Article in Frontiers in robotics and AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interactive human-machine systems aim to significantly enhance performance and reduce human workload by leveraging the combined strengths of humans and automated systems. In the state of the art, human-machine cooperation (HMC) systems are modeled in various interaction layers, e.g., the decision layer, trajectory layer, and action layer. The literature usually focuses on the action layer, assuming that there is no need for a consensus at the decision or trajectory layers. Only few studies deal with the interaction at the trajectory layer. None of the previous work has systematically examined the structure of communication for interaction between humans and machines beyond the action layer. Therefore, this paper proposes a graph representation based on a multi-agent system theory for human-machine cooperation. For this purpose, a layer model for human-machine cooperation from the literature is converted into a graph representation. Using our novel graph representation, the existence of communication loops can be demonstrated, which are necessary for emancipated cooperation. In contrast, a leader-follower structure does not possess a closed loop in this graph representation. The choice of the communication loop for emancipated cooperation is ambiguous and can take place via various closed loops at higher layers of human-machine interactions, which open new possibilities for the design of emancipated cooperative control systems. In a simulation, it is shown that emancipated cooperation is possible via three variants of communication loops and that a consensus on a common trajectory is found in each case. The results indicate that taking into account cooperative strategies at the trajectory layer can enhance the performance and effectiveness of human-machine systems.
Indexed as
Identifiers
What OpenQuestion holds
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.