Knowledge Commons of Institute of Automation,CAS
Grasp State Assessment of Deformable Objects Using Visual-Tactile Fusion Perception | |
Cui SW(崔少伟)1,2![]() ![]() ![]() ![]() ![]() | |
2020-05 | |
会议名称 | 2020 IEEE International Conference on Robotics and Automation (ICRA) |
会议日期 | 2022-5-31 |
会议地点 | Paris, France |
摘要 | Humans can quickly determine the force required to grasp a deformable object to prevent its sliding or excessive deformation through vision and touch, which is still a challenging task for robots. To address this issue, we propose a novel 3D convolution-based visual-tactile fusion deep neural network (C3D-VTFN) to evaluate the grasp state of various deformable objects in this paper. Specifically, we divide the grasp states of deformable objects into three categories of sliding, appropriate and excessive. Also, a dataset for training and testing the proposed network is built by extensive grasping and lifting experiments with different widths and forces on 16 various deformable objects with a robotic arm equipped with a wrist camera and a tactile sensor. As a result, a classification accuracy as high as 99.97% is achieved. Furthermore, some delicate grasp experiments based on the proposed network are implemented in this paper. The experimental results demonstrate that the C3D-VTFN is accurate and efficient enough for grasp state assessment, which can be widely applied to automatic force control, adaptive grasping, and other visual-tactile spatiotemporal sequence learning problems. |
学科门类 | 工学::控制科学与工程 |
DOI | 10.1109/ICRA40945.2020.9196787 |
URL | 查看原文 |
收录类别 | EI |
语种 | 英语 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48970 |
专题 | 多模态人工智能系统全国重点实验室_智能机器人系统研究 |
通讯作者 | Wang S(王硕) |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Cui SW,Wang R,Wei JH,et al. Grasp State Assessment of Deformable Objects Using Visual-Tactile Fusion Perception[C],2020. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Grasp State Assessme(3334KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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