# Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypes

arXiv: https://arxiv.org/abs/2602.03054 · HTML: https://mlsanity.com/paper/2602.03054/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 92 references that are in the map.
- First posted on arXiv 3 Feb 2026.

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

- [DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning](https://mlsanity.com/paper/2411.04983/) (2024)
- [Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey](https://mlsanity.com/paper/2503.12605/) (2025)
- [Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI](https://mlsanity.com/paper/2407.06886/) (2024)
- [Healthcare Robotics](https://mlsanity.com/paper/1704.03931/) (2017)
- [Edge Computing and its Application in Robotics: A Survey](https://mlsanity.com/paper/2507.00523/) (2025)
- [From Virtual Agents to Robot Teams: A Multi-Robot Framework Evaluation in High-Stakes Healthcare Context](https://mlsanity.com/paper/2506.03546/) (2025)
- [Humanoids in Hospitals: A Technical Study of Humanoid Robot Surrogates for Dexterous Medical Interventions](https://mlsanity.com/paper/2503.12725/) (2025)
- [Mapping While Following: 2D LiDAR SLAM in Indoor Dynamic Environments with a Person Tracker](https://mlsanity.com/paper/2204.08163/) (2022)
- [FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers' Preference Elicitation](https://mlsanity.com/paper/2403.06267/) (2024)
- [CRAFT@Large: Building Community Through Co-Making](https://mlsanity.com/paper/2410.23239/) (2024)

## Built on by (most cited first, 2 of 2)

- [Towards Considerate Human-Robot Coexistence: A Dual-Space Framework of Robot Design and Human Perception in Healthcare](https://mlsanity.com/paper/2604.04374/) (2026)
- [Finishing the Task Is Not Enough: Evaluating Agent Resilience and Considerate Participation under Accumulating Challenge](https://mlsanity.com/paper/2609.10724/) (2026)

## Abstract (arXiv)

Co-design is essential for grounding embodied artificial intelligence (AI) systems in real-world contexts, especially high-stakes domains such as healthcare. While prior work has explored multidisciplinary collaboration, iterative prototyping, and support for non-technical participants, few have interwoven these into a sustained co-design process. Such efforts often target one context and low-fidelity stages, limiting the generalizability of findings and obscuring how participants' ideas evolve. To address these limitations, we conducted a 14-week workshop with a multidisciplinary team of 22 participants, centered around how embodied AI can reduce non-value-added task burdens in three healthcare settings: emergency departments, long-term rehabilitation facilities, and sleep disorder clinics. We found that the iterative progression from abstract brainstorming to high-fidelity prototypes, supported by educational scaffolds, enabled participants to understand real-world trade-offs and generate more deployable solutions. We propose eight guidelines for co-designing more considerate embodied AI: attuned to context, responsive to social dynamics, mindful of expectations, and grounded in deployment. Project Page: https://byc-sophie.github.io/Towards-Considerate-Embodied-AI/