Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms

Huang, Hsu‐Chih; Xu, Sendren Sheng-Dong; Hsu, Huan-Shiuan

doi:10.1155/2014/358269

Cited by 7 publications

(5 citation statements)

References 22 publications

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“…Heuristic and meta-heuristic algorithm-based motion planning and tracking were also employed. [25,29,42,46] proposed an adaptive genetic algorithm for tracking the trajectory of a robot manipulator. Online optimizations method was proposed by [16] for trajectory tracking to overcome the limitation of the traditional methods.…”

Section: Introductionmentioning

confidence: 99%

Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

Kanagaraj

Masthan

2022

mendel

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In robot-assisted manufacturing or assembly, following a predefined path became a critical aspect. In general, inverse kinematics offers the solution to control the movement of manipulator while following the trajectory. The main problem with the inverse kinematics approach is that inverse kinematics are computationally complex. For a redundant manipulator, this complexity is further increased. Instead of employing inverse kinematics, the complexity can be reduced by using a heuristic algorithm. Therefore, a heuristic-based approach can be used to solve the inverse kinematics of the robot manipulator end effector, guaranteeing that the desired paths are accurately followed. This paper compares the performance of four such heuristic-based approaches to solving the inverse kinematics problem. They are Bat Algorithm (BAT), Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA). The performance of these algorithms is evaluated based on their ability to accurately follow a predefined trajectory. Extensive simulations show that BAT and GSA outperform PSO and WOA in all aspects considered in this work related to inverse kinematic problems.

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Section: Introductionmentioning

confidence: 99%

Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

Kanagaraj

Masthan

2022

mendel

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“…Various soft computing methods [19][20][21][22][23][24][25][26] based on the artificial neural network and genetic algorithm are also the research hotspots in recent years. A comparative study between different soft computing-based methods (artificial neural network, adaptive neuro-fuzzy inference system, and genetic algorithms) applied to the problem of inverse kinematics is presented in [19].…”

Section: Introductionmentioning

confidence: 99%

“…A genetic algorithm based on extreme learning machine and sequential mutation is presented in [20]. A hybrid Taguchi deoxyribonucleic acid (DNA) swarm intelligence for solving the inverse kinematic redundancy problem is presented in [21]. In [22], an online adaptive strategy based on the Lyapunov stability theory is presented to solve the inverse kinematics of redundant manipulators.…”

Section: Introductionmentioning

confidence: 99%

Two Optimized General Methods for Inverse Kinematics of 6R Robots Based on Machine Learning

Wang

Cao

Chen

et al. 2020

Mathematical Problems in Engineering

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For the 6R robot, there is no analytical solution for some configurations, so it is necessary to analyse inverse kinematics (IK) by the general solution method, which cannot achieve high precision and high speed as the analytical solution. With the expansion of application fields and the complexity of application scenarios, some robots with special configuration have become the research hotspot, and more high-speed and high-precision general algorithms are still being explored and studied. The present paper optimized two general solutions. Elimination is a numerical solution, which has high accuracy, but the solution process is complex and time-consuming. The present paper optimized the elimination method, derived the final matrix expression directly through complex coefficient extraction and simplifying operation, and realized one-step solution. The solving speed was reduced to 15% of the original, and the integrity of the method was supplemented. This paper proposed a new optimization method for the Gaussian damped least-squares method, in which the variable step-size coefficient is introduced and the machine learning method is used for the research. It was proved that, on the basis of guaranteeing the stability of motion, the average number of iterations can be effectively reduced and was only 4-5 times, effectively improving the solving speed.

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“…Some of the major studies are summarized as follows: (1) aiming to deal with some inherent flaws of DNA computing, such as adaptability [31] and instability [32]; (2) employing DNAs to realize some basic computing components and/or techniques, such as data storage [33], database operations [34], odd parity checker [35], half adder [36], encryption [37], and data hiding [38]; (3) utilizing DNAs to address some problems in real world, such as the inverse kinematics redundancy problem of six-degree-of-freedom humanoid robot arms [39], dynamic control of elevator systems [40], and hyperspectral remote sensing data/imagery [41, 42]. …”

Section: Introductionmentioning

confidence: 99%

Model Checking Temporal Logic Formulas Using Sticker Automata

Zhu

Cheng

2017

BioMed Research International

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As an important complex problem, the temporal logic model checking problem is still far from being fully resolved under the circumstance of DNA computing, especially Computation Tree Logic (CTL), Interval Temporal Logic (ITL), and Projection Temporal Logic (PTL), because there is still a lack of approaches for DNA model checking. To address this challenge, a model checking method is proposed for checking the basic formulas in the above three temporal logic types with DNA molecules. First, one-type single-stranded DNA molecules are employed to encode the Finite State Automaton (FSA) model of the given basic formula so that a sticker automaton is obtained. On the other hand, other single-stranded DNA molecules are employed to encode the given system model so that the input strings of the sticker automaton are obtained. Next, a series of biochemical reactions are conducted between the above two types of single-stranded DNA molecules. It can then be decided whether the system satisfies the formula or not. As a result, we have developed a DNA-based approach for checking all the basic formulas of CTL, ITL, and PTL. The simulated results demonstrate the effectiveness of the new method.

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Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms

Cited by 7 publications

References 22 publications

Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

Two Optimized General Methods for Inverse Kinematics of 6R Robots Based on Machine Learning

Model Checking Temporal Logic Formulas Using Sticker Automata

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