A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently

Multi-AUV Cooperative Target Hunting based on Improved Potential Field in a Surface-Water Environment

In this paper, target hunting aims to detect target and surround the detected target in a surface-water using Multiple Autonomous Underwater Vehicles (multi-AUV) in a given area. The main challenge in multi-AUV target hunting is the design of AUV\u27s motion path and coordination mechanism. To conduct the cooperative target hunting by multi-AUV in a surface-water environment, an integrated algorithm based on improved potential field (IPF) is proposed. First, a potential field function is established according to the information of the surface-water environment. Then, the dispersion degree, the homodromous degree, and district-difference degree are introduced to increase the cooperation of the multi-AUV system. Finally, the target hunting is solved by embedding the three kinds of degree into the potential field function. The simulation results show that the proposed approach is applicable and feasible for multi-AUV cooperative target hunting

A Bioinspired Neural Model Based Extended Kalman Filter for Robot SLAM

Robot simultaneous localization and mapping (SLAM) problem is a very important and challenging issue in the robotic field. The main tasks of SLAM include how to reduce the localization error and the estimated error of the landmarks and improve the robustness and accuracy of the algorithms. The extended Kalman filter (EKF) based method is one of the most popular methods for SLAM. However, the accuracy of the EKF based SLAM algorithm will be reduced when the noise model is inaccurate. To solve this problem, a novel bioinspired neural model based SLAM approach is proposed in this paper. In the proposed approach, an adaptive EKF based SLAM structure is proposed, and a bioinspired neural model is used to adjust the weights of system noise and observation noise adaptively, which can guarantee the stability of the filter and the accuracy of the SLAM algorithm. The proposed approach can deal with the SLAM problem in various situations, for example, the noise is in abnormal conditions. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach

Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

An Improved VFF Approach for Robot Path Planning in Unknown and Dynamic Environments

Robot path planning in unknown and dynamic environments is one of the hot topics in the field of robot control. The virtual force field (VFF) is an efficient path planning method for robot. However, there are some shortcomings of the traditional VFF based methods, such as the local minimum problem and the higher computational complexity, in dealing with the dynamic obstacle avoidance. In this paper, an improved VFF approach is proposed for the real-time robot path planning, where the environment is unknown and changing. An area ratio parameter is introduced into the proposed VFF based approach, where the size of the robot and obstacles are considered. Furthermore, a fuzzy control module is added, to deal with the problem of obstacle avoidance in dynamic environments, by adjusting the rotation angle of the robot. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Em direção ao desenho de um módulo social-inspirado para a tomada de decisões dos nós de uma rede Ad Hoc

Este artículo presenta el estado del arte preparado en un proyecto de investigación que propone la construcción de un módulo de software en nodos inalámbricos que adquieran la capacidad de decidir sobre su ingreso (o no ingreso) a una red Ad Hoc, y sobre la cantidad de recursos que van a aportar a ella, si deciden entrar, considerando datos que le proporciona la red acerca de los recursos disponibles y la cantidad de nodos, y acerca de parámetros internos como CPU, disco duro y procesador, entre otros, mediante un modelo matemático de toma de decisiones. El módulo debe poder interactuar con un intérprete en un nivel inferior y una entidad de nivel superior que equivale a un sistema distribuido. La investigación está enmarcada en el Sistema de Cómputo del grupo TLÖN de la Universidad Nacional de Colombia, el cual busca la aplicación de un paradigma social-inspirado en redes Ad Hoc.This article presents the state of the art derived from a research project where the construction of a software module related with the capability of the wireless nodes to decide whether or not to enter an ad hoc network, is proposed. If the decision is to enter, the amount of resources needed to provide the net is assessed by analyzing data provided for the network about the resources available and the number of nodes and internal parameters (CPU, hard disk, and processor, among others) through a mathematical model. The module developed should interact with an interpreter at a lower level and with a higher level entity, a distributed system. The research is supported by the computational system of the TLÖN group of the Universidad Nacional de Colombia, where its main purpose is to study the application of a social-inspired paradigm in ad hoc networks.Este artigo apresenta o estado da arte preparada em um projeto de pesquisa que propõe a construção de um módulo de software em nós sem fio que possam adquirir a capacidade de decidir sobre o seu ingresso (ou não ingresso) para uma rede ad hoc, e sobre a quantidade de recursos que irão somar à rede, se decidirem ingressar, considerando os dados fornecidos pela rede sobre os recursos disponíveis e o número de nós, e sobre os parâmetros internos, tais como CPU, disco rígido e processador, entre outros, através de um modelo matemático de tomada de decisões. O módulo deve ser capaz de interagir com um intérprete de nível inferior e uma entidade de nível superior equivalente a um sistema distribuído. A pesquisa está enquadrada no Sistema de Cômputo do grupo Tlön da Universidade Nacional de Colômbia, que visa a implementação de um paradigma social-inspirado em redes ad hoc

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties