# Uncertainty-Resilient Active Intention Recognition for Robotic Assistants

arXiv: https://arxiv.org/abs/2508.19150 · HTML: https://mlsanity.com/paper/2508.19150/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 33 references that are in the map.
- First posted on arXiv 26 Aug 2025.

## Builds on (most cited first, 7 of 7)

- [Robotic Control via Embodied Chain-of-Thought Reasoning](https://mlsanity.com/paper/2407.08693/) (2024)
- [Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects](https://mlsanity.com/paper/1809.10790/) (2018)
- [NViSII: A Scriptable Tool for Photorealistic Image Generation](https://mlsanity.com/paper/2105.13962/) (2021)
- [CoSTAR: Instructing Collaborative Robots with Behavior Trees and Vision](https://mlsanity.com/paper/1611.06145/) (2016)
- [Active Goal Recognition](https://mlsanity.com/paper/1909.11173/) (2019)
- [Mesh-based Object Tracking for Dynamic Semantic 3D Scene Graphs via Ray Tracing](https://mlsanity.com/paper/2408.04979/) (2024)
- [Towards Intention Recognition for Robotic Assistants Through Online POMDP Planning](https://mlsanity.com/paper/2411.17326/) (2024)

## Abstract (arXiv)

Purposeful behavior in robotic assistants requires the integration of multiple components and technological advances. Often, the problem is reduced to recognizing explicit prompts, which limits autonomy, or is oversimplified through assumptions such as near-perfect information. We argue that a critical gap remains unaddressed -- specifically, the challenge of reasoning about the uncertain outcomes and perception errors inherent to human intention recognition. In response, we present a framework designed to be resilient to uncertainty and sensor noise, integrating real-time sensor data with a combination of planners. Centered around an intention-recognition POMDP, our approach addresses cooperative planning and acting under uncertainty. Our integrated framework has been successfully tested on a physical robot with promising results.