GNN-based Decentralized Perception in Multirobot Systems for Predicting Worker Actions

Ali Imran, Giovanni Beltrame, David St-Onge
1/8/2025
cs.ROcs.AIcs.MA

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

In industrial environments, predicting human actions is essential for ensuring safe and effective collaboration between humans and robots. This paper introduces a perception framework that enables mobile robots to understand and share information about human actions in a decentralized way. The framework first allows each robot to build a spatial graph representing its surroundings, which it then shares with other robots. This shared spatial data is combined with temporal information to track human behavior over time. A swarm-inspired decision-making process is used to ensure all robots agree on a unified interpretation of the human's actions. Results show that adding more robots and incorporating longer time sequences improve prediction accuracy. Additionally, the consensus mechanism increases system resilience, making the multi-robot setup more reliable in dynamic industrial settings.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Collaborative Perception in Multi-Robot Systems: Case Studies in Household Cleaning and Warehouse Operations

89% match2024

XR-DT: Extended Reality-Enhanced Digital Twin for Safe Motion Planning via Human-Aware Model Predictive Path Integral Control

86% match2025

Seeing is Believing (and Predicting): Context-Aware Multi-Human Behavior Prediction with Vision Language Models

86% match2025

SPACE: A Python-based Simulator for Evaluating Decentralized Multi-Robot Task Allocation Algorithms

85% match1 repo272024

Few-Shot Inference of Human Perceptions of Robot Performance in Social Navigation Scenarios

85% match2025

Following the Human Thread in Social Navigation

85% match1 repo222026

Cite this paper

@article{imran2025gnnbased,
  title  = {GNN-based Decentralized Perception in Multirobot Systems for Predicting Worker Actions},
  author = {Ali Imran and Giovanni Beltrame and David St-Onge},
  year   = {2025},
  eprint = {2501.04193},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.04193v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2501.04193.svg)](https://codeofpaper.com/paper/2501.04193)

Discussion