Triboelectric Self-Powered Wearable Flexible Patch as 3D Motion Control Interface for Robotic Manipulator

ACS Nano ◽  
2018 ◽  
Vol 12 (11) ◽  
pp. 11561-11571 ◽  
Author(s):  
Tao Chen ◽  
Qiongfeng Shi ◽  
Minglu Zhu ◽  
Tianyiyi He ◽  
Lining Sun ◽  
...  
2021 ◽  
pp. 2100230
Author(s):  
Zhongda Sun ◽  
Minglu Zhu ◽  
Zixuan Zhang ◽  
Zhaocong Chen ◽  
Qiongfeng Shi ◽  
...  

2018 ◽  
Vol 18 (07) ◽  
pp. 1840017 ◽  
Author(s):  
QIN YAO ◽  
XUMING ZHANG

Flexible needle has been widely used in the therapy delivery because it can advance along the curved lines to avoid the obstacles like important organs and bones. However, most control algorithms for the flexible needle are still limited to address its motion along a set of arcs in the two-dimensional (2D) plane. To resolve this problem, this paper has proposed an improved duty-cycled spinning based three-dimensional (3D) motion control approach to ensure that the beveled-tip flexible needle can track a desired trajectory to reach the target within the tissue. Compared with the existing open-loop duty-cycled spinning method which is limited to tracking 2D trajectory comprised of few arcs, the proposed closed-loop control method can be used for tracking any 3D trajectory comprised of numerous arcs. Distinctively, the proposed method is independent of the tissue parameters and robust to such disturbances as tissue deformation. In the trajectory tracking simulation, the designed controller is tested on the helical trajectory, the trajectory generated by rapidly-exploring random tree (RRT) algorithm and the helical trajectory. The simulation results show that the mean tracking error and the target error are less than 0.02[Formula: see text]mm for the former two kinds of trajectories. In the case of tracking the helical trajectory, the mean tracking error target error is less than 0.5[Formula: see text]mm and 1.5[Formula: see text]mm, respectively. The simulation results prove the effectiveness of the proposed method.


Author(s):  
Kelvin Chen Chih Peng ◽  
William Singhose ◽  
Jonathan Fonseca

Payload oscillation inherent to all cranes makes it challenging for human operators to manipulate payloads quickly, accurately, and safely. A new type of crane control interface that allows an operator to drive a crane by moving his or her hand freely in space has been implemented on an industrial bridge crane. An image processing system tracks the movement of a glove worn on the operator’s hand and its position is then used to drive the crane. Matlab simulations of the crane dynamics and hand-motion control were compared with actual experimental data. The results show that a combination of aggressive PD gains and an input shaper is able to generate the desired characteristics of fast payload response and low residual oscillations.


2019 ◽  
Vol 24 (5) ◽  
pp. 2328-2340 ◽  
Author(s):  
Mohammad Jafarinasab ◽  
Shahin Sirouspour ◽  
Eric Dyer

2015 ◽  
Author(s):  
Karina Assolari Takano ◽  
Fabian Andres Lara Molina ◽  
Edson Hideki Koroishi

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