Aerosol Jet Printing of Strain Sensors for Soft Robotics
Aerosol Jet Printing of Strain Sensors for Soft Robotics
复制标题
用于软体机器人的应变传感器的气溶胶喷射打印
DOI：
10.1002/adem.202301275
复制
发表时间：
2023
影响因子：
3.6
通讯作者：
Karipoth P
中科院分区：
文献类型：
--
作者：
Karipoth P
软机器人领域正在迅速向包括可穿戴电子设备、假肢和生物医学设备在内的应用领域发展。这导致了对灵活的嵌入式高性能应变传感器的需求，以提供对这些机器人设备的静态配置和动态运动的实时反馈，最终实现智能操作所需的自主控制和结构监控水平。在这里，利用喷雾打印(AJP)技术在纤维纸上产生任意的压阻式应变传感器布局，适合直接集成到弹性软机器人中。一种定制的石墨烯纳米片状墨水的粘度约为2.70 CP，已被配方用于通过AJP优化雾化和导电痕迹的图案化。探索了在不同纸张基材上的单层和多层打印；打印轨道的标称电阻从272到4900 kΩ不等，具体取决于纸张类型和层数。在拉伸和压缩模式下，传感器表面的最大测量系数分别为24.2 ± 1.8和56.5 ± 4.5。为了证明将这种方法直接集成到软机器人技术中的可能性，应变传感器直接打印在气动软机器人夹持器的应变限制层上，以提供夹持器在高达80 m−1的曲率范围内的连续反馈。
The field of soft robotics is rapidly progressing toward applications including; wearable electronics, prosthetics, and biomedical devices. This is leading to demand for flexible, embedded high‐performance strain sensors to deliver real‐time feedback on the static configurations and dynamic motions of these robotic devices, to ultimately enable the levels of autonomous control and structural monitoring required for intelligent manipulation. Herein, aerosol jet printing (AJP) technology is utilized to generate arbitrary piezoresistive strain sensor layouts on fibrous paper suitable for direct integration into elastomeric soft robots. A custom graphene nanoplatelet ink with a viscosity of around 2.70 cP has been formulated for optimized atomization and patterning of conductive traces via AJP. Single and multilayer printing onto different paper substrates are explored; with the nominal resistance of the printed tracks varying from 272 to 4900 kΩ depending on paper type and number of layers. Maximum gauge factors of 24.2 ± 1.8 and 56.5 ± 4.5 are determined for sensor surfaces under tensile and compression modes, respectively. To demonstrate the possibility for direct integration of this approach for soft robotics, strain sensors are directly printed onto the strain‐limiting layer of a pneumatic soft robotic gripper, to provide continuous feedback of the gripper over curvatures up to 80 m−1.
DOI：
--
发表时间：
2020
期刊：
Lecture Notes in Electrical Engineering
影响因子：
--
作者：
H. Srinivasa Rao
通讯作者：
H. Srinivasa Rao