Evolutionary bi-criteria optimum design of robots based on task specifications

Saravanan, R.; Ramabalan, S.; Ebenezer, N. Godwin Raja; Natarajan, Rajesh

doi:10.1007/s00170-008-1483-8

Cited by 18 publications

(8 citation statements)

References 10 publications

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“…They performed the optimization at a fixed number of random poses simultaneously, and their objective function was to minimize the average minimum eigenvalue of the leg stiffness at each pose. Cui and Xiao [77] optimized the shape of single-link manipulators with the objective of maximizing natural frequencies with weight constraints using a GA. Saravanan et al [78] designed a robotic arm by optimizing the link cross section thicknesses using three different multi-objective evolutionary algorithms and the comparing the solutions of each. They also compared the effectiveness of performing the optimization using different link cross section shapes.…”

Section: Design For Robot Kineto-elastic Performance Requirementsmentioning

confidence: 99%

Kineto-elastic analysis of modular robot systems with component model updating

Mohamed¹

2021

Preprint

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This dissertation describes the kineto-elastic analysis and component structural dynamic model updating of serial modular reconfigurable robots (MRRs). In general, kineto-elastic analysis is concerned with the structural vibrations, elastic deflections, and torque transmissions of robots which undergo motion from one pose (position and orientation) to another. This work focuses on the kineto-elastic analysis of MRRs undergoing low-speed quasi-static motion. When determining an MRR's payload capacity, or designing MRR modules, the main difficulty is the large number of module configurations and the infinite number of poses within each configuration. Also, the kineto-elastic models of MRRs can become quite large with an increasing number of modules, thereby increasing the numerical complexity. Furthermore, the analytical models of individual MRR components may contain uncertainties, such as unknown stiffness and material parameters, which may lead to large errors for assembled MRR models. To alleviate these issues, a new framework was developed for the kineto-elastic analysis of MRR modules with an emphasis on assessing the worst-case poses. First, a combinatory search method was presented to reduce the computational burdens associated with determining the maximum payload capacity, and performing the module stiffness designs. This involved identifying the worst-case configuration and pose amongst a large number of configurations and infinite number of poses. Afterwards, it was demonstrated that the determination of an MRR's payload capacity, as well as the module stiffness designs, can be performed at the worst-case pose and configuration to satisfy a global set of kineto-elastic performance requirements for all remaining configurations. Next, a new component mode synthesis (CMS) model with fixed-free component boundaries was developed to reduce the sizes of kineto-elastic models, mimic natural link-joint connectivity, and allow experimental tests of joint modules in multiple poses to enable test-analysis model correlation. Finally, a novel method was created to update the uncertain model parameters of joint and link modules using frequency response data from component vibration tests in multiple poses (including the worst cases), with boundary conditions matching those from the CMS models. This procedure can completely avoid testing an entire assembly to perform model updating, and can provide accurate updated model results in any assembly pose.

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Section: Design For Robot Kineto-elastic Performance Requirementsmentioning

confidence: 99%

Kineto-elastic analysis of modular robot systems with component model updating

Mohamed¹

2021

Preprint

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“…To validate the computational efficiency and the modeling accuracy of the proposed method, multi-segment beam equivalent modeling method (Klimchik et al 2013;Luo et al 2012;Saravanan et al 2009) and finite TS1 TS2 TS3 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 L1 L2 Initial level 389 95 44.5 6 5 3.5 4.5 4.5 4.5 4.5 3.5 3 .5 3 3 203 202 Optimum level 389 135 44.5 3 3.5 1.5 4.5 6 5.5 5.5 4.5 2.5 2 2 223 222 (Kim et al 2016;Zhang et al 2017;Zhou and Bai 2015) are performed in this section. The CAD model of SHIR5-I Cobot is established by SolidWorks with the optimal level combination of the structural dimensions and joint components.…”

Section: Validationmentioning

confidence: 99%

“…The structural length index, the global conditioning index, and the modified dynamic conditioning index are used as objective functions in the global optimization design for optimal link dimensions by Hwang et al (2017). Based on task specifications, three optimization algorithms are used to minimize torque required for motion and maximize manipulability measure of robots subject to dynamic, kinematic constraints with the length and cross-sectional area parameters of links as design variables (Saravanan et al 2009). The global optimal design of a Delta robot with the dynamic performance constraint of minimal value of the first-order natural frequency is performed by Zhang and Song (2011), and the optimal objective of this method is the ratio of the sum of power consumption to the total movable mass.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective global optimum design of collaborative robots

Wang

Pan

2020

Struct Multidisc Optim

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Optimum design is proven significant for improving task performances of robotic manipulators under certain constraints. However, when it is utilized for collaborative robots (Cobots), there are still many challenges such as complex smooth surface links, time-varying kinematic configurations, computational expensiveness, and nonstructural parameter optimization. Therefore, based on orthogonal design experiment (ODE) and finite element substructure method (FESM), a multi-objective optimum design method of Cobots is proposed with the structural dimensions and parameterized joint components as the optimization variables and the natural frequency, the Cartesian stiffness, and the mass of the robot as optimization objectives. Firstly, to obtain multiple global performance indexes (GPIs) of robots in real-time and efficiently, the FESM model of Cobots is established which can preserve the accuracy of the finite element method (FEM) while ensuring the computational efficiency. Then, the gray relational analysis method (GRAM) is used to construct the multi-objective optimization function which includes the global first-order natural frequency index (GFNFI), the global elastic deformation index (GEDI), and the mass of robots. The ODE is constructed, and the structural dimensions and parameterized joint components are taken as influencing factors. According to the orthogonal array (OA), the degree of gray incidence under different levels of influencing factors is solved. And the optimal combination of influencing factor levels is obtained by range analysis (RA), which is used to guide the design of Cobots. Finally, a Cobot SHIR5-I is taken as an illustrative example to perform optimum design in this paper.

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“…NSGA-II algorithm has been widely used due to its good performance in exploring; Pareto set, which is obtained by NSGA-II algorithm, has good accuracy and dispersity. The NSGA-II procedure is shown in Figure 19 [7,40].…”

Section: (Iii) Consistency Checkingmentioning

confidence: 99%

“…Ghiorghe researched lightweight design on a RRR type industrial robot based on the FEM, used size parameters as design variables, and reduced the mass of robot [6]. Saravanan et al researched lightweight design on 2-link and 3-link planar robots, using minimized torque and maximized manipulability measure of robot as objectives, maximized deformation and joint angle as constraints, and lengths and cross-sectional area parameters of mechanical arm as design variables [7]. Guo et al researched lightweight design on manipulator elderly service robot based on the FEM, reducing the mass of manipulator under the condition of satisfying strength and stiffness requirements [8].…”

Section: Introductionmentioning

confidence: 99%

Multicriteria Optimization Design for End Effector Mounting Bracket of a High Speed and Heavy Load Palletizing Robot

Mei

Zang

et al. 2018

Mathematical Problems in Engineering

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End effector mounting bracket is an important load bearing part of high speed and heavy load palletizing robot, which is located at the most distant point in robot rotation radius and frequently works in complex conditions such as start-stop, switch direction, and acceleration and deceleration motion; therefore, optimizing design for its structure is beneficial to improve the dynamic performance of robotic system and reduce energy consumption. Firstly, finite element model of end effector mounting bracket was established, and its accuracy was verified by contrastive analysis of modal test result and finite element model. Secondly, through modal analysis, vibration response test, frequency response analysis, and the static analysis, taking inertia into account, the mass is minimized, the maximal stress is minimized, the maximal deformation is minimized, and the first natural frequency is maximized as the optimization objectives are determined; the design variables were selected by sensitivity analysis, taking their value range as the constraint conditions; approximation models of objective functions were established by the Box-Behnken design and the response surface methodology, and their reliability was validated; to determine weighting factor of each optimization objective, an analytic hierarchy process based on finite element analysis (FEA + AHP) method was put forward to improve the objectivity of comparison matrix; subsequently, the multicriteria optimization mathematical model was established by the methods mentioned above. Thirdly, the multicriteria optimization problem was solved by the NSGA-II algorithms and optimization results were obtained. Finally, the contrastive analysis results between optimized model and initial model showed that, in the case of the maximum stress and deformation within allowable values range, the mass reduction was 17.8%; meanwhile, the first natural frequency was increased, and vibration response characteristics of the entire structure were improved significantly. The validity of this optimization design method was verified.

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Evolutionary bi-criteria optimum design of robots based on task specifications

Cited by 18 publications

References 10 publications

Kineto-elastic analysis of modular robot systems with component model updating

Kineto-elastic analysis of modular robot systems with component model updating

Multi-objective global optimum design of collaborative robots

Multicriteria Optimization Design for End Effector Mounting Bracket of a High Speed and Heavy Load Palletizing Robot

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