Particle Swarm Optimization Based Parameter Identification Applied to a Target Tracker Robot with Flexible Joint

Sangdani, M. H.; Tavakolpour-Saleh, A.R.

doi:10.5829/ije.2020.33.09c.14

Cited by 4 publications

(3 citation statements)

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“…Thus, a tradeoff has to be made between RLT and the stresses the actuator may be subjected to during its working conditions. The developed actuator has potential applications such as smart harvesting of delicate agricultural produce (such as tomatoes) [40,41] and biomedical assistance to the elderly [42][43][44].…”

Section: Effects Of Geometric Parametric Variations On Maximum Stress...mentioning

confidence: 99%

Effects of Inflation Pressure and Wall Thickness on Gripping Force of Semi-Cylindrical Shaped Soft Actuator: Numerical Investigation

Deepak

Menon

D'Souza

et al. 2022

IJE

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Soft robotics using Pneumatic Network actuators (Pneu-Net) is a developing field that has a promising future for variety of applications involving delicate operations such as biomedical assistance. The interaction between geometry and the performance of the actuator is an important topic which has been studied by many researchers in this field. However, there is a lack of investigation on the relationship between gripping capability and geometrical parameters of soft actuators. Especially, there is a need to shed more light on the effects of wall thicknesses on the gripping force developed. In the present study, a semi-cylindrical chambered PneuNet soft actuator is numerically investigated to evaluate the effects of pressure and wall thickness variations on its performance characteristics. The results revealed that increasing the restraining layer thickness (RLT) aids the bending capability of the actuator whereas increasing the chamber wall thickness reduces it. Therefore, maximum bending of the actuator is achieved at the combinations of minimum wall thickness and maximum RLT. At these geometrical configurations of maximum bending, the deformation-pressure relationships followed a sigmoidal function and tended towards linearity with increasing wall thickness and decreasing RLT. The gripping force showed an exponential increase with increasing working pressures and wall thicknesses. The maximum gripping force increased cubically with increasing wall thicknesses at their respective maximum working pressures, which was modeled using a polynomial regression model (R 2 =99.79%).

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Section: Effects Of Geometric Parametric Variations On Maximum Stress...mentioning

confidence: 99%

Effects of Inflation Pressure and Wall Thickness on Gripping Force of Semi-Cylindrical Shaped Soft Actuator: Numerical Investigation

Deepak

Menon

D'Souza

et al. 2022

IJE

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show abstract

“…In this paper, we select the first solution to overcome this problem. To accomplish this method, scholars have conducted a great deal of studies and have reached the important point that particle filtering based on intelligent optimization mechanism of biological group is a new perspective [13,14]. In fact, in these methods, the particles in the particle filter are considered as individuals in biological clusters, and the particle distribution using the simulated biological cluster motion law is more reasonable.…”

Section: Introductionmentioning

confidence: 99%

Improved Simultaneous Localization and Mapping Estimation using Crow Search Algorithm Based Particle Filter

Abedini,

Jazayeriy,

Kazemitabar

2023

IJE

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Trajectory tracking and positioning are essential requirements in many areas, including robots and autonomous vehicles. In some cases, such as in areas where GPS signals are weak or not available, trajectory tracking is used as an alternative positioning system. In these cases, simultaneous localization and mapping (SLAM), is of great importance as it does not require prior knowledge and empirical offline fingerprint. SLAM can be combined with signal processing algorithms among which, particle filter stands out. However, challenges exist such as particle weights degradation and particles impoverishment that need to be dealt with. In fact, the loss of particle diversity for estimation has led to the lack of particles. To overcome this problem, one solution is to diversify the selection of particles after resampling. In this paper, we proposed a crow search algorithm (CSA) to overcome these issues and improve position estimation. The simulation results showed that this algorithm greatly improved the performance of fast SLAM.

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“…Performance of this method is evaluated through the numerical simulation. Parameters of a target tracker robot are identified through the particle swarm optimization (PSO) algorithm by Sangdani and Tavakolpour-Saleh [16]. Motion equations of robot are described with considering flexible joints.…”

Section: Introductionmentioning

confidence: 99%

Any-time randomized kinodynamic path planning algorithm in dynamic environments with application to quadrotor

2021

IJE

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Particle Swarm Optimization Based Parameter Identification Applied to a Target Tracker Robot with Flexible Joint

Cited by 4 publications

References 0 publications

Effects of Inflation Pressure and Wall Thickness on Gripping Force of Semi-Cylindrical Shaped Soft Actuator: Numerical Investigation

Effects of Inflation Pressure and Wall Thickness on Gripping Force of Semi-Cylindrical Shaped Soft Actuator: Numerical Investigation

Improved Simultaneous Localization and Mapping Estimation using Crow Search Algorithm Based Particle Filter

Any-time randomized kinodynamic path planning algorithm in dynamic environments with application to quadrotor

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