Mobile robot position control algorithm based on multiple ultrasonic distance sensors

2015 ◽  
Author(s):  
Baeksuk Chu
Keyword(s):  
Mobile Robot ◽  
Control Algorithm ◽  
Position Control ◽  
Robot Position

Frequency-division based hybrid force/position control of robotic arms manipulating in uncertain environments

2020 ◽  
Vol 47 (3) ◽  
pp. 445-452 ◽  
Author(s):  
Guanghui Liu ◽  
Lijin Fang ◽  
Bing Han ◽  
Hualiang Zhang
Keyword(s):  
Force Control ◽  
Control Algorithm ◽  
Position Control ◽  
Polynomial Interpolation ◽  
Industrial Robot ◽  
Estimation Algorithm ◽  
System Stability ◽  
Frequency Division ◽  
Content Type ◽  
Robot Position

Purpose This paper aims to propose a hybrid force/position control algorithm based on the stiffness estimation of the unknown environment. A frequency-division control scheme is developed to improve the applicability and reliability of the robot in welding, polishing and assembly. Design/methodology/approach The stiffness estimation algorithm with time-varying forgetting factors is used to improve the speed and accuracy of the unknown environmental estimation. The sensor force control and robot position control are adopted in different frequencies to improve system stability and communication compatibility. In the low frequency of sensor force control, the Kalman state observer is used to estimate the robot’s joints information, whereas the polynomial interpolation is used to ensure the smoothness of the high frequency of robot position control. Findings Accurate force control, as well as the system stability, is attained by using this control algorithm. Practical implications The entire algorithm is applied to a six-degrees-of-freedom industrial robot, and experiments are performed to confirm its applicability. Originality/value The frequency-division control strategy guarantees the control stability and improves the smoothness of the robot movement.

scholarly journals Mobile robot position control in environment with static obstacles

2020 ◽  
Vol 2 (2) ◽  
pp. 78-87
Author(s):  
Konstantinos Giannousakis ◽  
Anthony Tzes
Keyword(s):  
Mobile Robot ◽  
Position Control ◽  
Robot Position

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 Neural Network Based Contact Force Control Algorithm for Walking Robots

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 287
Author(s):  
Byeongjin Kim ◽  
Soohyun Kim
Keyword(s):  
Neural Network ◽  
Contact Force ◽  
Force Control ◽  
Control Algorithm ◽  
Position Control ◽  
Linear Quadratic Regulator ◽  
Walking Robots ◽  
Test Model ◽  
Linear Quadratic ◽  
Contact Force Control

Walking algorithms using push-off improve moving efficiency and disturbance rejection performance. However, the algorithm based on classical contact force control requires an exact model or a Force/Torque sensor. This paper proposes a novel contact force control algorithm based on neural networks. The proposed model is adapted to a linear quadratic regulator for position control and balance. The results demonstrate that this neural network-based model can accurately generate force and effectively reduce errors without requiring a sensor. The effectiveness of the algorithm is assessed with the realistic test model. Compared to the Jacobian-based calculation, our algorithm significantly improves the accuracy of the force control. One step simulation was used to analyze the robustness of the algorithm. In summary, this walking control algorithm generates a push-off force with precision and enables it to reject disturbance rapidly.

Identification and Model Predictive Position Control of Two Wheeled Inverted Pendulum Mobile Robot

2015 ◽  
Vol 73 (6) ◽  
Author(s):  
Amir A. Bature ◽  
Salinda Buyamin ◽  
Mohamad N. Ahmad ◽  
Mustapha Muhammad ◽  
Auwalu A. Muhammad
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Mobile Robot ◽  
Inverted Pendulum ◽  
Position Control ◽  
Superior Performance ◽  
System A ◽  
Wheeled Inverted Pendulum ◽  
Simulation Results ◽  
Real Plant

In order to predict and analyse the behaviour of a real system, a simulated model is needed. The more accurate the model the better the response is when dealing with the real plant. This paper presents a model predictive position control of a Two Wheeled Inverted Pendulum robot. The model was developed by system identification using a grey box technique. Simulation results show superior performance of the gains computed using the grey box model as compared to common linearized mathematical model. 

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