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Aiming at obtaining a high-quality global path for a mobile robot which works in complex environments, a modified particle swarm optimization (PSO) algorithm, named random-disturbance self-adaptive particle swarm optimization (RDSAPSO), is proposed in this paper.

A perturbed global updating mechanism is introduced to the global best position to avoid stagnation in RDSAPSO. Moreover, a new self-adaptive strategy is proposed to fine-tune the three control parameters in RDSAPSO to dynamically adjust the exploration and exploitation capabilities of RDSAPSO. Because the convergence of PSO is paramount and influences the quality of the generated path, this paper also analytically investigates the convergence of RDSAPSO and provides a convergence-guaranteed parameter selection principle for RDSAPSO. Finally, a RDSAPSO-based global path planning (GPP) method is developed, in which the feasibility-based rule is applied to handle the constraint of the problem.

In an attempt to validate the proposed method, it is compared against six state-of-the-art evolutionary methods under three different numerical simulations. The simulation results confirm that the proposed method is highly competitive in terms of the path optimality. Moreover, the computation time of the proposed method is comparable with those of the other compared methods.

Therefore, the proposed method can be considered as a vital alternative in the field of GPP.

This paper aims to optimize the stiffness coefficient of the elastic element for a passive waist assistive exoskeleton (WAE). There is a tradeoff between stiffness coefficient of elastic element of the exoskeleton and work efficiency of the wearer, because elastic element affects original bending motion of the wearer and the force requirement of erector spinae is compensated by the other muscles. However, there is no accepted conclusion on how to determine the proper stiffness coefficient, especially with respected to the effort of groups of muscles, not only erector spinae.

In this study, a consumption indicator based on muscle fatigue of seven muscles is proposed and a Bayesian-based human-in-the-loop optimization approach is adopted to optimize the stiffness coefficient. Pneumatic artificial muscles are used to replace the mechanical elastic part to adjust the assistive force automatically. The proposed optimization method is verified by the way of load-lifting experiments with three different conditions: without exoskeleton, with fixed air pressure and with optimized air pressure. Six subjects participated in the experiment and each experiment is performed in different day.

Compared with No-Exo condition and static assistance condition, the parameter-optimized waist exoskeleton averagely reduces muscle fatigue of the six subjects by 45.30 ± 29.14% and 30.94 ± 30.29%, respectively. The experimental results indicate that the proposed method is effective to reduce muscle fatigue during stoop lifting task.

This paper provides a novel cost function construction method based on muscle fatigue and muscle synergy for passive WAE stiffness optimization.

Food festivals are prevalent for those passionate about food experience globally. More importantly, feedback from food reviewers on mass media platforms has been becoming a critical factor in facilitating the decision-making process of tourists in particular cities. Moreover, stimulating local tourism activities, thanks to food festivals, prove advantageous to the well-being of local habitants. The purpose of this paper is to provide readers with a general overview of food festival research trends in tourist cities, as tourism has the potential to contribute to targets in Goals 8, 12 and 14 on sustainable consumption and production and the sustainable use of resources, respectively, (UNWTO: World Tourism Organization).

This study searched and filtered documents from the Scopus and Web of Science databases, as well as used bibliometric analysis and other mathematical and statistical methods, to better understand the food festival research context between 1970 and 2021. The carriers with mathematical and statistical methods. VOSviewer algorithm was used to identify critical input for visualizing bibliometric networks and to create a framework for this academic food festival research.

The findings are primarily related to pre and post-COVID-19 research on food festivals worldwide. Furthermore, using an inductive approach, this paper reveals the impact of food festivals in cities and tourist behaviors. According to the findings, the food festival research trends are about “food festivals,” “slow food festivals” and “local food festivals.” Factor analysis is one of the most common analyses in this type of research. Other studies could use the findings and limitations to select appropriate themes and analysis approaches for their research topics.

Research data sets are mainly from articles that may not account for all actual trends during this pandemic.

This review expects to provide insights into food festivals and help future researchers to recognize several research gaps such as the lack of research on food festival manufacturers and producers or the consistency in visitors' aspect research of quality service, visitors' loyal intentions, satisfaction and culinary experience. The tourism industry can find research trends of food festivals and issues following COVID-19 to find their management styles to fit the context of the post-COVID-19 pandemic, facilitating organizing a safe and effective food festival.