scholarly journals A force/motion control approach based on trajectory planning for industrial robots with closed control architecture

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Alejandro GutierreznGiles ◽  
Luis U. EvangelistanHernandez ◽  
Marco A. Arteaga ◽  
Carlos A. CruznVillar ◽  
Alejandro RodrigueznAngeles
Author(s):  
Alireza Nemati ◽  
Manish Kumar

In this paper, a nonlinear control of a tilting rotor quadcopter is presented. The overall control architecture is divided into two sub-controllers. The first controller is based on the feedback linearization control derived from the dynamic model of the tilting quadcopter. This controls the pitch, roll, and yaw motions required for movement along an arbitrary trajectory in space. The second controller is based on two PD controllers which are used to control the tilting of the quadcopter independently along the pitch and the yaw directions respectively. The overall control enables the quadcopter to combine tilting and movement along a desired trajectory simultaneously. Simulation studies are presented based on the developed nonlinear dynamic model of the tilting rotor quadcopter to demonstrate the validity and effectiveness of the overall control system for an arbitrary trajectory tracking.


Author(s):  
A. Meghdari ◽  
H. Sayyaadi

Abstract An optimization technique based on the well known Dynamic Programming Algorithm is applied to the motion control trajectories and path planning of multi-jointed fingers in dextrous hand designs. A three fingered hand with each finger containing four degrees of freedom is considered for analysis. After generating the kinematics and dynamics equations of such a hand, optimum values of the joints torques and velocities are computed such that the finger-tips of the hand are moved through their prescribed trajectories with the least time or/and energy to reach the object being grasped. Finally, optimal as well as feasible solutions for the multi-jointed fingers are identified and the results are presented.


Author(s):  
Aniruddha V. Shembekar ◽  
Yeo Jung Yoon ◽  
Alec Kanyuck ◽  
Satyandra K. Gupta

Additive manufacturing (AM) technologies have been widely used to fabricate 3D objects quickly and cost-effectively. However, building parts consisting of complex geometries with multiple curvatures can be a challenging process for the traditional AM system whose capability is restricted to planar-layered printing. Using 6-DOF industrial robots for AM overcomes this limitation by allowing materials to deposit on non-planar surfaces with desired tool orientation. In this paper, we present collision-free trajectory planning for printing using non-planar deposition. Trajectory parameters subject to surface curvature are properly controlled to avoid any collision with printing surface. We have implemented our approach by using a 6-DOF robot arm. The complex 3D structures with various curvatures were successfully fabricated, while avoiding any failures in joint movement, holding comparable build time and completing with a satisfactory surface finish.


2004 ◽  
Vol 23 (4) ◽  
pp. 703-715 ◽  
Author(s):  
T. Chettibi ◽  
H.E. Lehtihet ◽  
M. Haddad ◽  
S. Hanchi

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.


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