Human-mimetic Hand Control Method Aiming at Reproducing Human-to-Human Contact Force

2019 ◽  
Vol 2019 (0) ◽  
pp. 2A1-G06 ◽  
Author(s):  
Azumi UENO ◽  
Ikuo MIZUUCHI
Keyword(s):  
Contact Force ◽  
Control Method ◽  
Human Contact ◽  
Hand Control

scholarly journals Research and Ground Verification of the Force Compliance Control Method for Space Station Manipulator

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Bingshan Hu ◽  
Huanlong Chen ◽  
Liangliang Han ◽  
Hongliu Yu
Keyword(s):  
Real Time ◽  
Contact Force ◽  
Control Algorithm ◽  
Control Method ◽  
Impedance Control ◽  
Space Station ◽  
Gravity Compensation ◽  
Compliance Control ◽  
Experiment Platform ◽  
Dual Arm

The space station manipulator does lots of tasks with contact force/torque on orbit. To ensure the safety of the space station and the manipulator, the contact force/torque of manipulator must be controlled. Based on analyzing typical tasks’ working flows and force control requirements, such as ORU (orbit replacement unit) changeout and dual arm collaborative payload transport, an impedance control method based on wrist 6 axis force/torque feedback is designed. For engineering implementation of the impedance control algorithm, the discretization method and impedance control parameters selection principle are also studied. To verify the compliance control algorithm, a ground experiment platform adopting industrial manipulators is developed. In order to eliminate the influence of gravity, a real-time gravity compensation algorithm is proposed. Then, the correctness of real-time gravity compensation and force compliance control algorithm is verified on the experiment platform. Finally, the ORU replacement and dual arm collaborative payload transport experiments are done. Experimental results show that the force compliance control method proposed in this paper can control the contact force and torque at the end of the manipulator when executing typical tasks.

Hybrid Force-Position Humanoid Hand Control in 3D Virtual Environment

2015 ◽  
Vol 762 ◽  
pp. 91-97 ◽  
Author(s):  
Danut A. Bucur ◽  
Luige Vladareanu ◽  
Hong Nian Yu ◽  
Xian Chao Zhao ◽  
Stefan Dumitru
Keyword(s):  
Virtual Environment ◽  
3D Modeling ◽  
Position Control ◽  
Control Method ◽  
Robotic Hand ◽  
Simulation Environment ◽  
Software Packages ◽  
Hand Control ◽  
3D Virtual Environment ◽  
Humanoid Hand

This paper presents the workflow to create a robotic humanoid hand simulation environment using two top software packages and also the implementation of an intelligent hybrid force - position control method using neural networks for force closing operation of a humanoid robotic hand modeled in the 3D virtual environment. The benefits that the 3D modeling provides are described and then the results of the proposed method are presented. This approach allows studying the motion of the robotic system under different circumstances without any greater costs.

Contour tracking of an unknown planar object by regulating force for mobile robot navigation

Robotica ◽  
2006 ◽  
Vol 25 (3) ◽  
pp. 297-305 ◽  
Author(s):  
Seul Jung ◽  
Poongwoo Jeon ◽  
T. C. Hsia
Keyword(s):  
Mobile Robot ◽  
Contact Force ◽  
Control Method ◽  
Robot Navigation ◽  
Orientation Angle ◽  
Lateral Force ◽  
Wheeled Mobile Robot ◽  
Mobile Robot Navigation ◽  
Contour Tracking ◽  
Lateral Direction

SUMMARYIn this paper, a novel contour-tracking control method of an unknown planar object by lateral force regulation for wheeled mobile robot navigation is presented. The robot is required to follow the contour of an unknown object toward the goal position. Based on mobile robot dynamic equations, a force-control algorithm is proposed to maintain constant contact with a planar object. Measured contact force from an object is used not only to regulate a contact force in a lateral direction, but also to control the orientation angle of the robot to avoid collision with an object. Simulation and experiment of contour-tracking tasks of a wheeled mobile robot are conducted. Experimental results show that the contact force is well-regulated, and the robot arrives at the goal position successfully.

scholarly journals Adaptive Variable Parameter Impedance Control for Apple Harvesting Robot Compliant Picking

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Ji Wei ◽  
Ding Yi ◽  
Xu Bo ◽  
Chen Guangyu ◽  
Zhao Dean
Keyword(s):  
Control System ◽  
Contact Force ◽  
Control Method ◽  
Impedance Control ◽  
Viscoelastic Model ◽  
Variable Parameter ◽  
Response Speed ◽  
Self Tuning ◽  
Impedance Parameters ◽  
Harvesting Robot

In order to reduce the damage of apple harvesting robot to fruits and achieve compliant picking, an adaptive variable parameter impedance control method for apple harvesting robot compliant picking is proposed in this paper. Firstly, the Burgers viscoelastic model is used to characterize the rheological properties of apples and study the variation of mechanical properties of apple grasping at different speeds. Then, a force-based impedance control system is designed. On this basis, aiming at the influence of impedance controller parameters on contact force, three impedance parameters self-tuning functions are constructed to complete the design of an improved force-based impedance control system based on the hyperbolic secant function. The simulation and experimental results show that the proposed control makes the desired force smoother, and its overshoot is about 2.3%. The response speed is faster, and the adjustment time of contact force is shorter of about 0.48 s. The contact force overshoot is about 2%, which is 37.5% less than that of the traditional force-based impedance control. This research improves the control performance for apple harvesting robot compliant picking.

Adaptive stable grasping control strategy based on slippage detection

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yang Chen ◽  
Fuchun Sun
Keyword(s):  
Control System ◽  
Contact Force ◽  
Control Strategy ◽  
Control Method ◽  
Engineering Application ◽  
Stable State ◽  
Content Type ◽  
Circuit Components ◽  
Unknown Disturbance ◽  
Slippage Detection

Purpose The authors want to design an adaptive grasping control strategy without setting the expected contact force in advance to maintain grasping stable, so that the proposed control system can deal with unknown object grasping manipulation tasks. Design/methodology/approach The adaptive grasping control strategy is proposed based on bang-bang-like control principle and slippage detection module. The bang-bang-like control method is designed to find and set the expected contact force for the whole control system, and the slippage detection function is achieved by dynamic time warping algorithm. Findings The expected contact force can adaptively adjust in grasping tasks to avoid bad effects on the control system by the differences of prior test results or designers. Slippage detection can be recognized in time with variation of expected contact force manipulation environment in the control system. Based on if the slippage caused by an unexpected disturbance happens, the control system can automatically adjust the expected contact force back to the level of the previous stable state after a given time, and has the ability to identify an unnecessary increasing in the expected contact force. Originality/value Only contact force is used as feedback variable in control system, and the proposed strategy can save hardware components and electronic circuit components for sensing, reducing the cost and design difficulty of conducting real control system and making it easy to realize in engineering application field. The expected contact force can adaptively adjust due to unknown disturbance and slippage for various grasping manipulation tasks.

Development of Pneumatic Power Assist Splint “ASSIST” Operated by Human Intention

2005 ◽  
Vol 17 (5) ◽  
pp. 568-574 ◽  
Author(s):  
Daisuke Sasaki ◽  
◽  
Toshiro Noritsugu ◽  
Masahiro Takaiwa
Keyword(s):  
Contact Force ◽  
Input Signal ◽  
Control Method ◽  
Center Of Pressure ◽  
Wearable Device ◽  
Light Weight ◽  
Human Arm ◽  
Human Intention ◽  
Pneumatic Power ◽  
Soft Actuators

The purpose of this study is to develop a pneumatic power assist splint for a human arm. In the wearable device, a high human friendliness such as a light weight, a safety is required. The developed splint is constructed with soft actuators to confer a human friendliness. In this paper, the structure of ASSIST for a human arm is described. In addition, the control method based on a human intention is proposed. In the proposed method, a center of pressure calculated from contact force between the forearm and appliance is used as an intention input signal. Finally, the effectiveness of ASSIST is evaluated using EMG.

A NOVEL PROPORTIONAL AND SIMULTANEOUS CONTROL METHOD FOR PROSTHETIC HAND

2017 ◽  
Vol 17 (08) ◽  
pp. 1750120 ◽  
Author(s):  
XIN LI ◽  
QIANG HUANG ◽  
JINYING ZHU ◽  
WENTAO SUN ◽  
HAOTIAN SHE
Keyword(s):  
Time Delay ◽  
Control Method ◽  
Prosthetic Hand ◽  
Wrist Flexion ◽  
Simultaneous Control ◽  
Flexion Extension ◽  
Hand Control ◽  
System Input ◽  
And Performance ◽  
Semg Signals

This paper proposes a novel control method of using the surface electromyogram (sEMG) signals to predict the kinematics of hand and wrist, which will be applied in the prosthetic hand control. Prediction of movement in 3 degree-of-freedoms’ (DoFs’) (wrist flexion/extension (WFE), lateral abduction/adduction (LAA), and hand open/close (HOC)) is investigated in this paper. The proposed control method contains a time-delay recurrent neural network (TDRNN), adopting the previous prediction of the joint angles and the time-delay sEMG signals as the system input. This proposed method uses a batch training based on Levenberg–Marquardt (LM) algorithm to learn the weights of the TDRNN. The trained TDRNN is aimed to achieve simultaneous and proportional regression from human movements of the 3 DoFs to those of the prosthetic hand. Three able-bodied subjects are chosen to participate in the test and demonstrate its feasibility and performance. The offline test result R2 ranges between 0.81 and 0.94. The online test results show that TDRNN reacts faster, which verifies that the method proposed in this paper will be feasible and effective in prosthetic hand control.

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