paper-with-me

홈 › Papers

Using role-play and Hierarchical Task Analysis for designing human-robot interaction

2025-09-16 · Mattias Wingren, Sören Andersson, Sara Rosenberg, Malin Andtfolk, Susanne Hägglund, Prashani Jayasingha Arachchige, Linda Nyholm arxiv

We present the use of two methods we believe warrant more use than they currently have in the field of human-robot interaction: role-play and Hierarchical Task Analysis. Some of its potential is showcased through our use of them in an ongoing research project which entails developing a robot application meant to assist at a community pharmacy. The two methods have provided us with several advantages. The role-playing provided a controlled and adjustable environment for understanding the customers' needs where pharmacists could act as models for the robot's behavior; and the Hierarchical Task Analysis ensured the behavior displayed was modelled correctly and aided development through facilitating co-design. Future research could focus on developing task analysis methods especially suited for social robot interaction.

📄 PDF Abstract BibTeX arXiv:2509.13378

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

HIP: Hierarchical Point Modeling and Pre-training for Visual Information Extraction

2024-11-02 · Rujiao Long, Pengfei Wang, Zhibo Yang, Cong Yao

End-to-end visual information extraction (VIE) aims at integrating the hierarchical subtasks of VIE, including text spotting, word grouping, and entity labeling, into a unified framework. Dealing with the gaps among the …

Image ReconstructionOptical Character Recognition (OCR)Text Spotting

Designing Domain-Specific Agents via Hierarchical Task Abstraction Mechanism

2025-11-21 · Kaiyu Li, Jiayu Wang, Zhi Wang, Hui Qiao 외 arxiv

LLM-driven agents, particularly those using general frameworks like ReAct or human-inspired role-playing, often struggle in specialized domains that necessitate rigorously structured workflows. Fields such as remote sens…

Hierarchical Graph Pooling with Structure Learning

2019-11-14 · Zhen Zhang, Jiajun Bu, Martin Ester, Jianfeng Zhang 외

Graph Neural Networks (GNNs), which generalize deep neural networks to graph-structured data, have drawn considerable attention and achieved state-of-the-art performance in numerous graph related tasks. However, existing…

Graph ClassificationGraph Neural NetworkRepresentation Learning

Identity-Driven Hierarchical Role-Playing Agents

2024-07-28 · Libo Sun, Siyuan Wang, Xuanjing Huang, Zhongyu Wei

Utilizing large language models (LLMs) to achieve role-playing has gained great attention recently. The primary implementation methods include leveraging refined prompts and fine-tuning on role-specific datasets. However…

Set the Stage: Enabling Storytelling with Multiple Robots through Roleplaying Metaphors

2025-08-03 · Tyrone Justin Sta Maria, Faith Griffin, Jordan Aiko Deja arxiv

Gestures are an expressive input modality for controlling multiple robots, but their use is often limited by rigid mappings and recognition constraints. To move beyond these limitations, we propose roleplaying metaphors …