scholarly journals Editorial: On the Planning, Control, and Perception of Soft Robotic End-Effectors

2021 ◽  
Vol 8 ◽  
Author(s):  
Giuseppe Averta ◽  
Cosimo Della Santina ◽  
Fanny Ficuciello ◽  
Maximo A. Roa ◽  
Matteo Bianchi
Keyword(s):  
End Effectors

scholarly journals Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3498
Author(s):  
Youqiang Zhang ◽  
Cheol-Su Jeong ◽  
Minhyo Kim ◽  
Sangrok Jin
Keyword(s):  
Control Algorithm ◽  
Position Control ◽  
Friction Model ◽  
Surgical Instruments ◽  
Control Input ◽  
End Effector ◽  
Motor Current ◽  
Direct Teaching ◽  
End Effectors ◽  
Teaching Operation

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and handle surgical instruments. It also presents a force-free control algorithm for the direct teaching of end effectors. The bidirectional telescopic mechanism can actively transmit force both upwards and downwards by staggering the wires on both sides. In order to estimate and control torque via motor current without a force/torque sensor, the gravity model and friction model of the device are derived through repeated experiments. The LuGre model is applied to the friction model, and the static and dynamic parameters are obtained using a curve fitting function and a genetic algorithm. Direct teaching control is designed using a force-free control algorithm that compensates for the estimated torque from the motor current for gravity and friction, and then converts it into a position control input. Direct teaching operation sensitivity is verified through hand-guiding experiments.

scholarly journals Modeling and evaluating beat gestures for social robots

2021 ◽  
Author(s):  
Unai Zabala ◽  
Igor Rodriguez ◽  
José María Martínez-Otzeta ◽  
Elena Lazkano
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Desirable Feature ◽  
Quantitative Results ◽  
Path Lengths ◽  
End Effectors ◽  
The One ◽  
Made In

AbstractNatural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemented by the Fréchet Gesture Distance (FGD) that aims to measure the fidelity of the generated gestures with respect to the provided ones. Results show that the described system is able to learn natural gestures just by observation and improves the one developed with a simpler motion capture system. The quantitative results are sustained by questionnaire based human evaluation.

scholarly journals Magnetic Driven Two-Finger Micro-Hand with Soft Magnetic End-Effector for Force-Controlled Stable Manipulation in Microscale

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 410
Author(s):  
Dan Liu ◽  
Xiaoming Liu ◽  
Pengyun Li ◽  
Xiaoqing Tang ◽  
Masaru Kojima ◽  
...  
Keyword(s):  
Magnetic Force ◽  
Force Feedback ◽  
Soft Magnetic ◽  
End Effector ◽  
Force Microscopy ◽  
System A ◽  
Atomic Force ◽  
Afm Probe ◽  
End Effectors ◽  
Fixed End

In recent years, micromanipulators have provided the ability to interact with micro-objects in industrial and biomedical fields. However, traditional manipulators still encounter challenges in gaining the force feedback at the micro-scale. In this paper, we present a micronewton force-controlled two-finger microhand with a soft magnetic end-effector for stable grasping. In this system, a homemade electromagnet was used as the driving device to execute micro-objects manipulation. There were two soft end-effectors with diameters of 300 μm. One was a fixed end-effector that was only made of hydrogel, and the other one was a magnetic end-effector that contained a uniform mixture of polydimethylsiloxane (PDMS) and paramagnetic particles. The magnetic force on the soft magnetic end-effector was calibrated using an atomic force microscopy (AFM) probe. The performance tests demonstrated that the magnetically driven soft microhand had a grasping range of 0–260 μm, which allowed a clamping force with a resolution of 0.48 μN. The stable grasping capability of the magnetically driven soft microhand was validated by grasping different sized microbeads, transport under different velocities, and assembly of microbeads. The proposed system enables force-controlled manipulation, and we believe it has great potential in biological and industrial micromanipulation.

Dynamic Grasping for Object Picking Using Passive Zero-DOF End-Effectors

2021 ◽  
Vol 6 (2) ◽  
pp. 3089-3096
Author(s):  
Caio Mucchiani ◽  
Mark Yim
Keyword(s):  
End Effectors

scholarly journals A Roadmap towards Standards for Neurally Controlled End Effectors

2021 ◽  
pp. 1-1
Author(s):  
Andrew Paek ◽  
Justin Brantley ◽  
Akshay Sujatha Ravindran ◽  
Kevin Nathan ◽  
Yongtian He ◽  
...  
Keyword(s):  
End Effectors

scholarly journals Deviation Tolerance Performance Evaluation and Experiment of Picking End Effector for Famous Tea

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 128
Author(s):  
Yingpeng Zhu ◽  
Chuanyu Wu ◽  
Junhua Tong ◽  
Jianneng Chen ◽  
Leiying He ◽  
...  
Keyword(s):  
Success Rate ◽  
Negative Pressure ◽  
Evaluation Method ◽  
Orthogonal Experiment ◽  
Spatial Position ◽  
End Effector ◽  
Significance Level ◽  
Growth Environment ◽  
End Effectors ◽  
Average Success Rate

Accurately obtaining the posture and spatial position of tea buds through machine vision and other technologies is difficult due to the small size, different shapes, and complex growth environment of tea buds. Therefore, end effectors are prone to problems, such as picking omission and picking error. This study designs a picking end effector based on negative pressure guidance for famous tea. This end effector uses negative pressure to guide tea buds in a top-down manner, thereby correcting their posture and spatial position. Therefore, the designed end effector has deviation tolerance performance that can improve the picking success rate. The pre-experiment is designed, the tip of apical bud is referred to as the descent position, and the negative pressure range is determined to be 0.6 to 0.9 kPa. A deviation tolerance orthogonal experiment is designed. Experimental results show that various experimental factors are ranked in terms of the significance level of the effect on the average success rate, and the significance ranking is as follows: negative pressure (P) > pipe diameter (D) > descent speed (V). An evaluation method of deviation tolerance performance is presented, and the optimal experiment factor-level combination is determined as: P = 0.9 kPa, D = 34 mm, V = 20 mm/s. Within the deviation range of a 10 mm radius, the average success rate of the negative pressure guidance of the end effector is 97.36%. The designed end effector can be applied to the intelligent picking of famous tea. This study can provide a reference for the design of similar picking end effectors for famous tea.

scholarly journals Suppress Vibration on Robotic Polishing with Impedance Matching

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 59
Author(s):  
Junjie Dai ◽  
Chin-Yin Chen ◽  
Renfeng Zhu ◽  
Guilin Yang ◽  
Chongchong Wang ◽  
...  
Keyword(s):  
Contact Force ◽  
Force Control ◽  
Impedance Control ◽  
Impedance Matching ◽  
Industrial Robots ◽  
Contact Phase ◽  
Dynamic Tracking ◽  
Force Tracking ◽  
The Difference ◽  
End Effectors

Installing force-controlled end-effectors on the end of industrial robots has become the mainstream method for robot force control. Additionally, during the polishing process, contact force stability has an important impact on polishing quality. However, due to the difference between the robot structure and the force-controlled end-effector, in the polishing operation, direct force control will have impact during the transition from noncontact to contact between the tool and the workpiece. Although impedance control can solve this problem, industrial robots still produce vibrations with high inertia and low stiffness. Therefore, this research proposes an impedance matching control strategy based on traditional direct force control and impedance control methods to improve this problem. This method’s primary purpose is to avoid force vibration in the contact phase and maintain force–tracking performance during the dynamic tracking phase. Simulation and experimental results show that this method can smoothly track the contact force and reduce vibration compared with traditional force control and impedance control.

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