# ROS-Causal: A ROS-based Causal Analysis Framework for Human-Robot Interaction Applications

arXiv: https://arxiv.org/abs/2402.16068 · HTML: https://mlsanity.com/paper/2402.16068/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 29 references that are in the map.
- First posted on arXiv 25 Feb 2024.

## Builds on (most cited first, 10 of 10)

- [Detecting causal associations in large nonlinear time series datasets](https://mlsanity.com/paper/1702.07007/) (2017)
- [DYNOTEARS: Structure Learning from Time-Series Data](https://mlsanity.com/paper/2002.00498/) (2020)
- [Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets](https://mlsanity.com/paper/2003.03685/) (2020)
- [Causal Reasoning in Simulation for Structure and Transfer Learning of Robot Manipulation Policies](https://mlsanity.com/paper/2103.16772/) (2021)
- [Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios](https://mlsanity.com/paper/2302.10135/) (2023)
- [Causal Discovery of Dynamic Models for Predicting Human Spatial Interactions](https://mlsanity.com/paper/2210.16535/) (2022)
- [CAR-DESPOT: Causally-Informed Online POMDP Planning for Robots in Confounded Environments](https://mlsanity.com/paper/2304.06848/) (2023)
- [Using Causal Analysis to Learn Specifications from Task Demonstrations](https://mlsanity.com/paper/1903.01267/) (2019)
- [Towards a Causal Probabilistic Framework for Prediction, Action-Selection & Explanations for Robot Block-Stacking Tasks](https://mlsanity.com/paper/2308.06203/) (2023)
- [Towards Probabilistic Causal Discovery, Inference & Explanations for Autonomous Drones in Mine Surveying Tasks](https://mlsanity.com/paper/2308.10047/) (2023)

## Built on by (most cited first, 4 of 4)

- [Experimental Evaluation of ROS-Causal in Real-World Human-Robot Spatial Interaction Scenarios](https://mlsanity.com/paper/2406.04955/) (2024)
- [Exploring Causality for HRI: A Case Study on Robotic Mental Well-being Coaching](https://mlsanity.com/paper/2503.11684/) (2025)
- [Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments](https://mlsanity.com/paper/2504.11901/) (2025)
- [Estimating the Causal Impact of Social Navigation Signals in Corridor Scenarios](https://mlsanity.com/paper/2610.16411/) (2026)

## Abstract (arXiv)

Deploying robots in human-shared spaces requires understanding interactions among nearby agents and objects. Modelling cause-and-effect relations through causal inference aids in predicting human behaviours and anticipating robot interventions. However, a critical challenge arises as existing causal discovery methods currently lack an implementation inside the ROS ecosystem, the standard de facto in robotics, hindering effective utilisation in robotics. To address this gap, this paper introduces ROS-Causal, a ROS-based framework for onboard data collection and causal discovery in human-robot spatial interactions. An ad-hoc simulator, integrated with ROS, illustrates the approach's effectiveness, showcasing the robot onboard generation of causal models during data collection. ROS-Causal is available on GitHub: https://github.com/lcastri/roscausal.git.