scholarly journals Force Sensing for Multi-Legged Walking Robots: Theory and Experiments Part 2: Force Control of Legged Vehicles

10.5772/4735 ◽  
2006 ◽  
Author(s):  
A. Schneider ◽  
U. Schmucker
Keyword(s):  
Force Control ◽  
Walking Robots ◽  
Force Sensing ◽  
Theory And 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.

Robot force control without dynamic model: theory and experiments

Robotica ◽  
2012 ◽  
Vol 31 (1) ◽  
pp. 149-171 ◽  
Author(s):  
Juan C. Rivera-Dueñas ◽  
Marco A. Arteaga-Pérez
Keyword(s):  
Model Theory ◽  
Contact Surface ◽  
Force Control ◽  
Control Algorithm ◽  
Velocity Measurements ◽  
Unit Quaternion ◽  
End Effector ◽  
Simulation Results ◽  
The Many ◽  
Theory And Experiments

SUMMARYAmong the many challenges to deal with, when a robot is interacting with its environment, friction at the contact surface and/or at the joints is one of the most important to be considered. In this paper we propose a control algorithm for the tracking of position and force (unconstrained orientation case only) of a manipulator end-effector that does not require the robot model for implementation. This characteristic has the advantage of making it capable to compensate friction effects without any previous estimation. Furthermore, no velocity measurements are needed, and the unit quaternion is employed for orientation control. Experimental and simulation results are provided.

FORCE SENSING AND CONTROL DURING MOVEMENT AND OBJECT MANIPULATION IN MERO WALKING ROBOTS

2013 ◽  
Author(s):  
ION ION ◽  
ADRIAN CURAJ ◽  
AURELIAN VASILE ◽  
DUMITRU IULIA ◽  
STAMATESCU GRIGORE
Keyword(s):  
Object Manipulation ◽  
Walking Robots ◽  
Force Sensing ◽  
And Control

An efficient foot-force distribution algorithm for quadruped walking robots

Robotica ◽  
2000 ◽  
Vol 18 (4) ◽  
pp. 403-413 ◽  
Author(s):  
Debao Zhou ◽  
K. H. Low ◽  
Teresa Zielinska
Keyword(s):  
Force Control ◽  
Computation Time ◽  
Optimization Method ◽  
The Body ◽  
Walking Robots ◽  
Force Distribution ◽  
Active Force ◽  
Distribution Method ◽  
Walking Machine ◽  
Active Force Control

One of the important issues of walking machine active force control is a successful distribution of the body force to the feet to prevent leg slippage. In this paper, a new force distribution method, the Friction Constraint Method (FriCoM), is introduced. The force distribution during the walking of a typical quadruped crawl gait is analyzed by using the FriCoM. Computation results show that the distributed forces of the feet are continuous during the walking. This reflects the change of the force distribution during actual conditions. The comparison with a pseudo-inverse method shows that the FriCoM is more practical. The FriCom also requires less computation time than that by an incremental optimization method. Some problems, such as the singularity in the application of the FriCoM, are discussed. The FriCoM will be used in the active force control of a quadruped robot that is taken as a platform for the research on the study of terrain adaptation.

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