scholarly journals GlobDesOpt: A Global Optimization Framework for Optimal Robot Manipulator Design

IEEE Access ◽  
2022 ◽  
pp. 1-1
Author(s):  
Francesco Cursi ◽  
Weibang Bai ◽  
Eric M. Yeatman ◽  
Petar Kormushev
Keyword(s):  
Global Optimization ◽  
Robot Manipulator ◽  
Optimization Framework ◽  
Manipulator Design

Optimization in the Design and Control of Robotic Manipulators: A Survey

1989 ◽  
Vol 42 (4) ◽  
pp. 117-128 ◽  
Author(s):  
S. S. Rao ◽  
P. K. Bhatti
Keyword(s):  
Optimal Control ◽  
Robot Manipulator ◽  
Research Effort ◽  
Industrial Robot ◽  
Load Capacity ◽  
Robotic Manipulators ◽  
Optimization Techniques ◽  
Highly Nonlinear ◽  
Manipulator Design ◽  
And Control

Robotics is a relatively new and evolving technology being applied to manufacturing automation and is fast replacing the special-purpose machines or hard automation as it is often called. Demands for higher productivity, better and uniform quality products, and better working environments are primary reasons for its development. An industrial robot is a multifunctional and computer-controlled mechanical manipulator exhibiting a complex and highly nonlinear behavior. Even though most current robots have anthropomorphic configurations, they have far inferior manipulating abilities compared to humans. A great deal of research effort is presently being directed toward improving their overall performance by using optimal mechanical structures and control strategies. The optimal design of robot manipulators can include kinematic performance characteristics such as workspace, accuracy, repeatability, and redundancy. The static load capacity as well as dynamic criteria such as generalized inertia ellipsoid, dynamic manipulability, and vibratory response have also been considered in the design stages. The optimal control problems typically involve trajectory planning, time-optimal control, energy-optimal control, and mixed-optimal control. The constraints in a robot manipulator design problem usually involve link stresses, actuator torques, elastic deformation of links, and collision avoidance. This paper presents a review of the literature on the issues of optimum design and control of robotic manipulators and also the various optimization techniques currently available for application to robotics.

Structured Motion Planning in the Local Configuration Space

Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 81-92 ◽  
Author(s):  
A. M. S. Zalzala ◽  
A. S. Morris
Keyword(s):  
Configuration Space ◽  
Robot Manipulator ◽  
Time History ◽  
Geometric Constraints ◽  
Polynomial Splines ◽  
Time Motion ◽  
Local Configuration ◽  
Travelling Time ◽  
Physical Limitations ◽  
Manipulator Design

SUMMARYThe minimum-time motion of robot manipulators is solved by defining a suitable time history for the arm end-effector to traverse. As the planning is performed in the configuration space, the uniqueness of the proposed algorithm emerges from the combination of both cubic and quadratic polynomial splines. Furthermore, the highly efficient time optimisation procedure could be applied to local segments of each joint trajectory, leading to a significant reduction of the travelling time. In addition, the ability to perform a search in the work space is granted, exploiting all possible options for an optimum motion. The method proposed considers all realistic physical limitations inherent in the manipulator design, in addition to any geometric constraints imposed on the path. Simulation programs have been written, and results are reported for the Unimation PUMA 560 robot manipulator.

Detecting dense crowds of microbes from microscope images in a global optimization framework

Optik ◽  
2016 ◽  
Vol 127 (1) ◽  
pp. 76-80 ◽  
Author(s):  
Ye Liu ◽  
Shuohong Wang ◽  
Hao Gao ◽  
Baoyun Wang
Keyword(s):  
Global Optimization ◽  
Optimization Framework ◽  
Microscope Images ◽  
Dense Crowds

UNIFICATION OF PR REGION FLOORPLANNING AND FINE-GRAINED PLACEMENT FOR DYNAMIC PARTIALLY RECONFIGURABLE FPGAS

2013 ◽  
Vol 22 (04) ◽  
pp. 1350020 ◽  
Author(s):  
RUINING HE ◽  
GUOQIANG LIANG ◽  
YUCHUN MA ◽  
YU WANG ◽  
JINIAN BIAN
Keyword(s):  
Global Optimization ◽  
Design Method ◽  
Critical Path ◽  
Design Flow ◽  
Path Delay ◽  
Wire Length ◽  
Fine Grained ◽  
Effective Strategies ◽  
Optimization Framework ◽  
Current Design

Dynamic Partially Reconfiguration (DPR) designs provide additional benefits compared to traditional FPGA application. However, due to the lack of support from automatic design tools in current design flow, designers have to manually define the dimensions and positions of Partially Reconfigurable Regions (PR Regions). The following fine-grained placement for system modules is also limited because it takes the floorplanning result as a rigid region constraint. Therefore, the manual floorplanning is laborious and may lead to inferior fine-grained placement results. In this paper, we propose to integrate PR Region floorplanning with fine-grained placement to achieve the global optimization of the whole DPR system. Effective strategies for tuning PR Region floorplanning and apposite analytical evaluation models are customized for DPR designs to handle the co-optimization for both PR Regions and static region. Not only practical reconfiguration cost and specific reconfiguration constraints for DPR system are considered, but also the congestion estimation can be relaxed by our approach. Especially, we established a two-stage stochastic optimization framework which handles different objectives in different optimization stages so that automated floorplanning and global optimization can be achieved in reasonable time. Experimental results demonstrate that due to the flexibility benefit from the unification of PR Region floorplanning and fine-grained placement, our approach can improve 20.9% on critical path delay, 24% on reconfiguration delay, 12% on congestion, and 8.7% on wire length compared to current DPR design method.

Sign in / Sign up

Export Citation Format

Share Document