A snake robot with mixed gaits capability

Snake robots are mostly designed based on single mode of locomotion. However, single mode gait most of the time fails to work effectively when they are required to work in different cluttered environment with different measures of complexity. As a solution, mixed mode locomotion is proposed in this paper by synchronizing serpentine gait for unconstricted workspace and wriggler gait for narrow space environment through development of a simple gait transition algorithm. This study includes the investigation on kinematics analysis followed by dynamics analysis while considering related structural constraints for both gaits. This approach utilized speed of the serpentine gait for open area operation and exploits narrow space access capability of the wriggler gait. Hence, this approach in such a way increases motion flexibility in view of the fact that the snake robot is capable of changing its mode of locomotion according to the working environment

Impact of initialization of a modified particle swarm optimization on cooperative source searching

Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environments and rigid searching constraints is an example of application where swarm robotics can be applied. Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. Improper parameter selection may lead to a premature convergence and thus robots will fail (i.e., low success rate) to locate the source within the given searching constraints. Additionally, target overshooting and improper initialization strategies may lead to a nonoptimal (i.e., take longer time to converge) target searching. In this study, a modified PSO and three different initializations strategies (i.e., random, equidistant and centralized) were proposed. The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. Additionally, the findings also indicate that the random initialization give better searching success compared to equidistant and centralize initialization

A systematic literature review on the use of podcasts in education among university students

Technology such as multimedia, particularly podcasts, is becoming more widely used in educational settings. The podcasts have been utilized at many levels of education, including elementary, secondary, and tertiary education. Along with this, many articles were written and published about the use of podcasts in education among university students. Our main objective in this study is to examine the use of podcasts in higher education among university students by systematically searching the Scopus database for papers relevant to the study. Eighteen papers were chosen and retrieved, then meticulously studied to uncover the new themes that have been classified as the result. The review found that podcasts have a favorable impact on university students and help them better understand the learning process. It also highlights the limits in its deployment that need to be addressed in order to improve the teaching and learning process

An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization

Swarm robotics is a study of how to organize a relatively large number of simple robots to achieve a robust, flexible and scalable solution for a given task. Searching a source with a complex spatial distribution pattern is one of the possible swarm robotics tasks. In a source searching task, two possible scenarios can occur: source detected and source not detected. In this study, a complete solution to the two scenarios through an adaptive algorithm switching strategy is explored. Firstly, to detect the source, a Source Detection Algorithm (SDA) known as a Distributed Lévy Flight (DLF) is proposed. To improve exploration performance of the individual agent, a turning angle limit and boundary reflection is introduced in DLF. In order to optimize search space exploration and to maintain inter-robot communication connectivity at swarm level, a dispersion algorithm based on attraction and repulsion force is proposed. Secondly, to trace the source to its approximate location, a Source Tracing Algorithm (STA) known as an Asynchronous Dynamically Adjustable Particle Swarm Optimization (ADAPSO) is suggested. The ADAPSO parameters are adaptively and asynchronously adjusted based on feedback informations to improve convergence speed, to avoid robot trapped into local optima and to minimize target overshooting. In addition, the ADAPSO position update equation is modified to anticipate position adjustment to ensure communication connectivity. To adaptively switches between the two algorithms, an adaptive switching algorithm based on a Generalized Likelihood Ratio Test (GLRT) is proposed. To demonstrate the algorithm switching principle, underwater acoustic source localization using a swarm of Autonomous Surface Vehicles (ASVs) is considered. By considering the ASVs as swarm robotics testing platforms, each algorithm is evaluated and benchmarked against several existing algorithms through simulation studies. The obtained results show that the performance of the DLF for source detection outperformed other benchmark algorithms in term of search space exploration capability and the time taken to detect the source. The ADAPSO for source tracing achieved better tracing performance with better success rate and reduced the time taken to trace the source to its approximate location compared to the benchmark algorithms. Finally, the feasibility of the proposed algorithms for underwater acoustic source localization is confirmed through simulation and experimentation where the achieved average accuracy of source position estimation is 0.4 m and 4.2 m, respectively

A combined systematic and metaheuristic approach for cooperative underwater acoustic source localization by a group of autonomous surface vehicles

2434-2443Underwater acoustic source localization is important in many underwater applications. However, due to the intensity declination of the acoustic signal as the distance from the source increases, the possibility to detect and localize the source using a single surface platform become harder. This paper presents an underwater acoustic source localization strategy by a group of autonomous surface vehicles (ASVs) using a combined systematic and metaheuristic searching methods. The proposed localization strategy consists of two phases known as a source detection phase (based on a systematic searching method) and a source tracing phase (based on a metaheuristic searching method) implemented when none of the ASVs detect the presents of the acoustic source and when at least one of the ASVs detect the presents of the source, respectively. A formation based and a Particle Swarm Optimization (PSO) is used as a systematic and metaheuristic search method, respectively. The reliability of the proposed localization strategy is demonstrated through a series of a simulation studies