Design and Analysis of a Fully Actuated Cable-Driven Joint for Hyper-Redundant Robots with Optimal Cable Routing

2021 ◽  
pp. 1-13
Author(s):  
Paolo Guardiani ◽  
Daniele Ludovico ◽  
Alessandro Pistone ◽  
Haider Abidi ◽  
Isiah Zaplana ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimization Method ◽  
Robot Arm ◽  
Redundant Robot ◽  
Redundant Robots ◽  
Routing Optimization ◽  
Novel Design

Abstract Cable-driven hyper-redundant robots have been adopted in many fields for accessing harsh and confined environments that maybe inaccessible or dangerous for humans. The cable actuation strategy makes the robot hardware safer and increases the robot payload reducing its weight. In this paper, a novel design of a fully actuated cable-driven hyper-redundant robot has been proposed. This solution is a pulleyless design that decreases the mechanical complexity, allowing to reduce the robot arm diameter and avoid tension losses on the cables during the motion. Three different joint designs have been taken into account and experiments have been carried to study their performances. The kinematics for n-joint robot has been formulated and a cable routing optimization method based on genetic algorithm have been proposed and applied to a five-joints robot.

scholarly journals Compliant behaviour of redundant robot arm - experiments with null-space

2015 ◽  
Vol 12 (1) ◽  
pp. 81-98
Author(s):  
Petar Petrovic ◽  
Nikola Lukic ◽  
Ivan Danilov
Keyword(s):  
Stiffness Matrix ◽  
Jacobian Matrix ◽  
Null Space ◽  
Joint Space ◽  
Robot Arm ◽  
Kinematic Redundancy ◽  
Redundant Robot ◽  
Redundant Robots ◽  
Compliant Behavior ◽  
Congruent Transformation

This paper presents theoretical and experimental aspects of Jacobian nullspace use in kinematically redundant robots for achieving kinetostatically consistent control of their compliant behavior. When the stiffness of the robot endpoint is dominantly influenced by the compliance of the robot joints, generalized stiffness matrix can be mapped into joint space using appropriate congruent transformation. Actuation stiffness matrix achieved by this transformation is generally nondiagonal. Off-diagonal elements of the actuation matrix can be generated by redundant actuation only (polyarticular actuators), but such kind of actuation is very difficult to realize practically in technical systems. The approach of solving this problem which is proposed in this paper is based on the use of kinematic redundancy and nullspace of the Jacobian matrix. Evaluation of the developed analytical model was done numerically by a minimal redundant robot with one redundant d.o.f. and experimentally by a 7 d.o.f. Yaskawa SIA 10F robot arm.

Using a new GA-based multiobjective optimization technique for the design of robot arms

Robotica ◽  
1998 ◽  
Vol 16 (4) ◽  
pp. 401-414 ◽  
Author(s):  
Carlos A. Coello Coello ◽  
Alan D. Christiansen ◽  
Arturo Hernández Aguirre
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Ad Hoc ◽  
Optimization Technique ◽  
Hybrid Approach ◽  
Optimization Method ◽  
Robot Arm ◽  
Genetic Operators ◽  
Point Representation ◽  
A New Technique

This paper presents a hybrid approach to optimize the counterweight balancing of a robot arm. A new technique that combines an artificial intelligence technique called the genetic algorithm (GA) and the weighted min-max multiobjective optimization method is proposed. These techniques are included in a system developed by the authors, called MOSES, which is intended to be used as a tool for engineering design optimization. The results presented here show how the new proposed technique can get better trade-off solutions and a more accurate Pareto front for this highly non-convex problem using an ad-hoc floating point representation and traditional genetic operators. Finally, a methodology to compute the ideal vector using a genetic algorithm is presented. It is shown how with a very simple dynamic approach to adjust the parameters of the GA, it is possible to obtain better results than those previously reported in the literature for this problem.

scholarly journals A Robot Arm Design Optimization Method by Using a Kinematic Redundancy Resolution Technique

Robotics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Omar W. Maaroof ◽  
Mehmet İsmet Can Dede ◽  
Levent Aydin
Keyword(s):  
Design Optimization ◽  
Mechanical Design ◽  
Optimization Method ◽  
Robot Arm ◽  
Redundancy Resolution ◽  
Redundant Robots ◽  
Virtual Joints ◽  
Self Motion

Redundancy resolution techniques have been widely used for the control of kinematically redundant robots. In this work, one of the redundancy resolution techniques is employed in the mechanical design optimization of a robot arm. Although the robot arm is non-redundant, the proposed method modifies robot arm kinematics by adding virtual joints to make the robot arm kinematically redundant. In the proposed method, a suitable objective function is selected to optimize the robot arm’s kinematic parameters by enhancing one or more performance indices. Then the robot arm’s end-effector is fixed at critical positions while the redundancy resolution algorithm moves its joints including the virtual joints because of the self-motion of a redundant robot. Hence, the optimum values of the virtual joints are determined, and the design of the robot arm is modified accordingly. An advantage of this method is the visualization of the changes in the manipulator’s structure during the optimization process. In this work, as a case study, a passive robotic arm that is used in a surgical robot system is considered and the task is defined as the determination of the optimum base location and the first link’s length. The results indicate the effectiveness of the proposed method.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

Enterprise distribution routing optimization with soft time windows based on genetic algorithm

2021 ◽  
pp. 1-11
Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun
Keyword(s):  
Genetic Algorithm ◽  
Customer Satisfaction ◽  
Optimization Problems ◽  
Rapid Development ◽  
Time Windows ◽  
Theory And Practice ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
A Company

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.

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