Optimal Force Distribution for Payload Positioning Using a Planar Dual-Arm Robot

1989 ◽  
Vol 111 (2) ◽  
pp. 205-210 ◽  
Author(s):  
C. R. Carignan ◽  
D. L. Akin
Keyword(s):  
Differential Equations ◽  
Parameter Optimization ◽  
Optimization Technique ◽  
Force Distribution ◽  
Torque Distribution ◽  
Optimal Force ◽  
Dual Arm Robot ◽  
Arm Transport ◽  
Dual Arm ◽  
Optimal Force Distribution

This paper presents a parameter optimization technique for deciding the force distribution on a payload being transported along a predetermined trajectory using two planar manipulator arms. The methodology begins by transforming the singular dynamics of two-arm transport to an ordinary set of differential equations and then proceeds to obtain a relation between the torques exerted by each arm. This relation is then used in a quadratic torque cost which is subsequently minimized to yield an optimal torque distribution. Significant savings in energy were found to occur when the arms were allowed to interact by transmission of forces through the payload. Even more significant are the savings found over one-arm transport of payloads where the arm torques are fixed by the prescribed trajectory.

A Neurofuzzy Knowledge Based Architecture for Robotic Hand Manipulation Forces Learning

2013 ◽  
Vol 3 (2) ◽  
pp. 16-38 ◽  
Author(s):  
Ebrahim Mattar
Keyword(s):  
Force Distribution ◽  
Robotic Hand ◽  
Knowledge Based ◽  
Optimal Force ◽  
Learning Technique ◽  
Optimization Formulation ◽  
Hand Grasp ◽  
Optimal Set ◽  
Dextrous Hand ◽  
Optimal Force Distribution

Optimal distribution of forces for manipulation by a robot hand, is a hard computational issue, specifically once a whole hand grasp is needed. It becomes a complicated issue, once a robotic hand is equipped with human like deformable sensory touching materials. For computing optimal set of manipulation forces, grip transform and inverse hand Jacobian play major roles for such purposes. This manuscript is discussing a Neurofuzzy learning technique for learning optimal force distribution by a dextrous hand. For learning purposes, optimal set of forces patterns were gathered in advanced using optimization formulation technique. After that, to let a Neurofuzzy system to learn the nonlinear kinematics-dynamics relations needed for force distribution. This is done by considering the computational requirements for the inverse hand Jacobian, in addition to the interaction between hand fingers and the object. Training patterns clustering, and generation of the fuzzy initial memberships, and updated shape of memberships, are considered as vital information to build upon for more reasoning of fuzzy interrelation. The technique is novel in a sense, that the adopted Neurofuzzy architecture was transparent in terms of revealing the learned hand optimal forces if then rules.

scholarly journals Minimizing the Energy Consumption for a Hexapod Robot Based on Optimal Force Distribution

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 5393-5406 ◽  
Author(s):  
Guanyu Wang ◽  
Liang Ding ◽  
Haibo Gao ◽  
Zongquan Deng ◽  
Zhen Liu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Force Distribution ◽  
Hexapod Robot ◽  
Optimal Force ◽  
Optimal Force Distribution

An optimal force distribution scheme for cooperating multiple robot manipulators

Robotica ◽  
1993 ◽  
Vol 11 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Yong Dal Shin ◽  
Myung Jin Chung
Keyword(s):  
Efficient Method ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
Force Distribution ◽  
Weak Point ◽  
Contact Points ◽  
Optimal Force ◽  
Distribution Scheme ◽  
Equality And Inequality Constraints ◽  
Optimal Force Distribution

SUMMARYIn this paper, we suggest an optimal force distribution scheme by weak point force minimization and we also present an efficient method to solve the problem. The concept of a weak point is a generalized one which is applicable to any points of interest, as well as joints or contact points between end-effectors and an object. The problem is formulated by a quadratic objective function of the forces exerted at weak points subject to the linear equality and inequality constraints, and its optimal solution is obtained by an efficient method. As regards the solution of the problem, the original problem is reformulated to a reduced order dual problem after the equality constraints are eliminated by force decomposition.

Geometric parameter identification of a dual-arm robot by using closed-chain constraint and optimization technique

2017 ◽  
Vol 232 (7) ◽  
pp. 1294-1302 ◽  
Author(s):  
Wu-Te Yang ◽  
Kuan-Lin Li ◽  
Kuei-Yuan Chan ◽  
Pei-Chun Lin
Keyword(s):  
Optimization Technique ◽  
Constraint Equation ◽  
Calibration Method ◽  
Kinematic Parameter ◽  
Motion Generation ◽  
Positioning Accuracy ◽  
Closed Chain ◽  
Controller Performance ◽  
Dual Arm Robot ◽  
Dual Arm

The positioning accuracy of the empirical robot manipulators is determined by various factors, such as kinematic accuracy, structure rigidity, and controller performance. Here, we report on the development of a new and straightforward technique to calibrate the kinematic parameters of a dual-arm robot under uncertainty. In comparison with other techniques, which generally rely on using other instruments to calibrate the manipulators, the proposed method utilizes the intrinsic characteristics of the dual-arm robot for calibration. In particular, when the two arms grasp each other, a formed closed chain can be operated as the constraint equation for the kinematic parameter optimization of the two arms. In the optimization process, the dual-arm robot has to pose in various configurations to yield better performance, and thus a motion generation strategy of the dual-arm robot is proposed, where one arm serves as the master to track the designated trajectory and the other arm serves as the slave to track the motion of the master arm by using a compliance control strategy. The proposed calibration method was experimentally validated, and the results confirm that the positioning accuracy of both arms can be improved.

scholarly journals COVID-19 em Londrina-PR: Modelo SEIR com Otimização de Parâmetros

2021 ◽  
Vol 42 (1 Supl) ◽  
pp. 45
Author(s):  
Eliandro Rodrigues Cirilo ◽  
Paulo Laerte Natti ◽  
Pedro Henrique Valério de Godoi ◽  
Andina Lerma ◽  
Vitor Matias ◽  
...  
Keyword(s):  
Differential Equations ◽  
Parameter Optimization ◽  
Compartmental Model ◽  
Optimization Technique ◽  
Relevant Information ◽  
Present Moment ◽  
Infected People ◽  
Transmission Rates ◽  
City Hall ◽  
Over Time

The first cases of COVID-19 in Londrina-PR were manifested in March 2020 and the disease lasts until the present moment. We aim to inform citizens in a scientific way about how the disease spreads. The present work seeks to describe the behavior of the disease over time. We started from a compartmental model of ordinary differential equations like SEIR to find relevant information such as: transmission rates and prediction of the peak of infected people. We used the data released by city hall of Londrina to carry out simulations in periods of 14 days, applying a parameter optimization technique to obtain results with thegreatest possible credibility.

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