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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.03741 |
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| _version_ | 1866912377974292480 |
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| author | Zhao, Qianwen Roy, Rajarshi Spurlock, Chad Lister, Kevin Wang, Long |
| author_facet | Zhao, Qianwen Roy, Rajarshi Spurlock, Chad Lister, Kevin Wang, Long |
| contents | Recently, there has been a growing interest in rescue robots due to their vital role in addressing emergency scenarios and providing crucial support in challenging or hazardous situations where human intervention is difficult. However, very few of these robots are capable of actively engaging with humans and undertaking physical manipulation tasks. This limitation is largely attributed to the absence of tools that can realistically simulate physical interactions, especially the contact mechanisms between a robotic gripper and a human body. In this letter, we aim to address key limitations in current developments towards robotic casualty manipulation. Firstly, we present an integrative simulation framework for casualty manipulation. We adapt a finite element method (FEM) tool into the grasping and manipulation scenario, and the developed framework can provide accurate biomechanical reactions resulting from manipulation. Secondly, we conduct a detailed assessment of grasping stability during casualty grasping and manipulation simulations. To validate the necessity and superior performance of the proposed high-fidelity simulation framework, we conducted a qualitative and quantitative comparison of grasping stability analyses between the proposed framework and the state-of-the-art multi-body physics simulations. Through these efforts, we have taken the first step towards a feasible solution for robotic casualty manipulation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_03741 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A High-Fidelity Simulation Framework for Grasping Stability Analysis in Human Casualty Manipulation Zhao, Qianwen Roy, Rajarshi Spurlock, Chad Lister, Kevin Wang, Long Robotics Recently, there has been a growing interest in rescue robots due to their vital role in addressing emergency scenarios and providing crucial support in challenging or hazardous situations where human intervention is difficult. However, very few of these robots are capable of actively engaging with humans and undertaking physical manipulation tasks. This limitation is largely attributed to the absence of tools that can realistically simulate physical interactions, especially the contact mechanisms between a robotic gripper and a human body. In this letter, we aim to address key limitations in current developments towards robotic casualty manipulation. Firstly, we present an integrative simulation framework for casualty manipulation. We adapt a finite element method (FEM) tool into the grasping and manipulation scenario, and the developed framework can provide accurate biomechanical reactions resulting from manipulation. Secondly, we conduct a detailed assessment of grasping stability during casualty grasping and manipulation simulations. To validate the necessity and superior performance of the proposed high-fidelity simulation framework, we conducted a qualitative and quantitative comparison of grasping stability analyses between the proposed framework and the state-of-the-art multi-body physics simulations. Through these efforts, we have taken the first step towards a feasible solution for robotic casualty manipulation. |
| title | A High-Fidelity Simulation Framework for Grasping Stability Analysis in Human Casualty Manipulation |
| topic | Robotics |
| url | https://arxiv.org/abs/2404.03741 |