Abstract
Versatility in engineering means adaptability and multi-functionality. For robotic automation, it signifies the ability to handle diverse tasks, easily switch between different operations, and thrive in changing environments. The current gap lies in developing agreed-upon frameworks and metrics that are both quantitative and context-appropriate, capturing not just mechanical capabilities but also cognitive adaptability, integration complexity, and economic value.
In this paper, we present the Design and Learning Research Group's (DLRG) solution for the euROBIN Manipulation Skill Versatility Challenge (MSVC) at IROS 2024 in Abu Dhabi, UAE. The MSVC, held annually since 2021, is part of the euROBIN project that seeks to advance transferrable robot skills for the circular economy by autonomously performing tasks such as object localization, insertion, door operation, circuit probing, and cable management. We approached the standardized task board provided by event organizers that mimics industrial testing procedures by structurally decomposing the task into subtask skills. We created a custom dashboard with drag-and-drop code blocks to streamline development and adaptation, enabling rapid code refinement and task restructuring, complementing the default remote web platform that records the performance. Our system completed the task board in 28.2 sec in the lab (37.2 sec on-site), nearly tripling the efficiency over the averaged best time of 83.5 sec by previous teams and bringing performance closer to a human baseline of 16.3 sec. By implementing subtasks as reusable code blocks, we facilitated the transfer of these skills to a distinct scenario, successfully removing a battery from a smoke detector with minimal reconfiguration.
We also provide suggestions for future research and industrial practice on robotic versatility in manipulation automation through globalized competitions, interdisciplinary efforts, standardization initiatives, and iterative testing in the real world to ensure that it is measured in a meaningful, actionable way.
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BibTeX (Download)
@online{Han2025TransferrableRobot,
title = {Transferrable Robot Skills Approaching Human-Level Versatility in Automated Task Board Manipulation},
author = {Xudong Han and Haoran Sun and Ning Guo and Sheng Ge and Jia Pan and Fang Wan and Chaoyang Song},
url = {https://msvc-dlrg.github.io/},
year = {2024},
date = {2024-12-15},
abstract = {Versatility in engineering means adaptability and multi-functionality. For robotic automation, it signifies the ability to handle diverse tasks, easily switch between different operations, and thrive in changing environments. The current gap lies in developing agreed-upon frameworks and metrics that are both quantitative and context-appropriate, capturing not just mechanical capabilities but also cognitive adaptability, integration complexity, and economic value.
In this paper, we present the Design and Learning Research Group's (DLRG) solution for the euROBIN Manipulation Skill Versatility Challenge (MSVC) at IROS 2024 in Abu Dhabi, UAE. The MSVC, held annually since 2021, is part of the euROBIN project that seeks to advance transferrable robot skills for the circular economy by autonomously performing tasks such as object localization, insertion, door operation, circuit probing, and cable management. We approached the standardized task board provided by event organizers that mimics industrial testing procedures by structurally decomposing the task into subtask skills. We created a custom dashboard with drag-and-drop code blocks to streamline development and adaptation, enabling rapid code refinement and task restructuring, complementing the default remote web platform that records the performance. Our system completed the task board in 28.2 sec in the lab (37.2 sec on-site), nearly tripling the efficiency over the averaged best time of 83.5 sec by previous teams and bringing performance closer to a human baseline of 16.3 sec. By implementing subtasks as reusable code blocks, we facilitated the transfer of these skills to a distinct scenario, successfully removing a battery from a smoke detector with minimal reconfiguration.
We also provide suggestions for future research and industrial practice on robotic versatility in manipulation automation through globalized competitions, interdisciplinary efforts, standardization initiatives, and iterative testing in the real world to ensure that it is measured in a meaningful, actionable way.},
note = {Submitted to IEEE Robotics and Automation Practics for the Special Collection "Autonomous Robotic Grasping and Manipulation in Real-World Applications."},
keywords = {Authorship - Corresponding, Status - Under Review},
pubstate = {forthcoming},
tppubtype = {online}
}
