Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks
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Abstract (arXiv)
Collaborative robots require effective human intention estimation to safely and smoothly work with humans in less structured tasks such as industrial assembly, where human intention continuously changes. We propose the concept of intention tracking and introduce a collaborative robot system that concurrently tracks intentions at hierarchical levels. The high-level intention is tracked to estimate human's interaction pattern and enable robot to (1) avoid collision with human to minimize interruption and (2) assist human to correct failure. The low-level intention estimate provides robot with task-related information. We implement the system on a UR5e robot and demonstrate robust, seamless and ergonomic human-robot collaboration in an ablative pilot study of an assembly use case. Our robot demonstrations and videos are available at urlhttps://sites.google.com/view/hierarchicalintentiontracking.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Mar 2022.
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Citing papers per year: 2024: 2; 2025: 2.
4 papers.
- 2024LIT: Large Language Model Driven Intention Tracking for Proactive Human-Robot Collaboration -- A Robot Sous-Chef Applicationcited by 3
- 2025Bi-VLA: Bilateral Control-Based Imitation Learning via Vision-Language Fusion for Action Generationcited by 3
- 2024Hierarchical Deep Learning for Intention Estimation of Teleoperation Manipulation in Assembly Taskscited by 1
- 2025Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Modelscited by 1
- 2025Bi-VLA: Bilateral Control-Based Imitation Learning via Vision-Language Fusion for Action Generation23 Sep 2025
- 2025Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models17 Jun 2025
- 2024LIT: Large Language Model Driven Intention Tracking for Proactive Human-Robot Collaboration -- A Robot Sous-Chef Application19 Jun 2024
- 2024Hierarchical Deep Learning for Intention Estimation of Teleoperation Manipulation in Assembly Tasks28 Mar 2024