Efficient PID Controller based Hexapod Wall Following Robot

This paper presents a design of wall followingbehaviour for hexapod robot based on PID controller. PIDcontroller is proposed here because of its ability to controlmany cases of non-linear systems. In this case, we proposed aPID controller to improve the speed and stability of hexapodrobot movement while following the wall. In this paper, PIDcontroller is used to control the robot legs, by adjusting thevalue of swing angle during forward or backward movement tomaintain the distance between the robot and the wall. Theexperimental result was verified by implementing the proposedcontrol method into actual prototype of hexapod robot

Efficient PID Controller based Hexapod Wall Following Robot

This paper presents a design of wall following behaviour for hexapod robot based on PID controller. PID controller is proposed here because of its ability to control many cases of non-linear systems. In this case, we proposed a PID controller to improve the speed and stability of hexapod robot movement while following the wall. In this paper, PID controller is used to control the robot legs, by adjusting the value of swing angle during forward or backward movement to maintain the distance between the robot and the wall. The experimental result was verified by implementing the proposed control method into actual prototype of hexapod robot

A Novel Relative Navigation Control Strategy Based on Relation Space Method for Autonomous Underground Articulated Vehicles

This paper proposes a novel relative navigation control strategy based on the relation space method (RSM) for articulated underground trackless vehicles. In the RSM, a self-organizing, competitive neural network is used to identify the space around the vehicle, and the spatial geometric relationships of the identified space are used to determine the vehicle’s optimal driving direction. For driving control, the trajectories of the articulated vehicles are analyzed, and data-based steering and speed control modules are developed to reduce modeling complexity. Simulation shows that the proposed RSM can choose the correct directions for articulated vehicles in different tunnels. The effectiveness and feasibility of the resulting novel relative navigation control strategy are validated through experiments

Study on sensible beginning divided-search enhanced Karnik-Mendel algorithms for centroid type-reduction of general type-2 fuzzy logic systems

General type-2 fuzzy logic systems (GT2 FLSs) on the basis of alpha-plane representation of GT2 fuzzy sets (FSs) have attracted considerable attention in recent years. For the kernel type-reduction (TR) block of GT2 FLSs, the enhanced Karnik-Mendel (EKM) algorithm is the most popular approach. This paper proposes the sensible beginning divided-search EKM (SBDEKM) algorithms for completing the centroid TR of GT2 FLSs. Computer simulations are provided to show the performances of the SBDEKM algorithms. Compared with EKM algorithms and sensible beginning EKM (SBEKM) algorithms, the SBDEKM algorithms have almost the same accuracies and better computational efficiency

Intelligent Robotics Navigation System: Problems, Methods, and Algorithm

This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments

Análise de uma estratégia de coordenação bio-inspirada de múltiplos robôs para a tarefa de vigilância em ambientes desconhecidos

Uma estratégia distribuída de coordenação modelada de acordo com uma versão modificada do algoritmo que simula o comportamento de formigas guia robôs móveis para região não exploradas e regiões não recentemente exploradas. Em pesquisa anterior, a aplicação da estratégia confirmou que comportamentos de exploração e vigilância emergem do comportamento individual do agente. A estratégia é capaz de adaptar o sistema proposto para situações em que o número de robôs ou a estrutura do ambiente mudam. Nesta pesquisa, uma variação paramétrica da estratégia é empregada com base nos fenômenos de evaporação e propagação do feromônio. Resultados experimentais demonstram que diferentes configurações do fenômeno afetam o comportamento de exploração e vigilância. Os resultados mostram a eficiência da estratégia para realizar tarefas cooperativas.FAPESPCNPqCAPE

Mobile Robot Navigation in Static and Dynamic Environments using Various Soft Computing Techniques

The applications of the autonomous mobile robot in many fields such as industry, space, defence and transportation, and other social sectors are growing day by day. The mobile robot performs many tasks such as rescue operation, patrolling, disaster relief, planetary exploration, and material handling, etc. Therefore, an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments. The present research focuses on the design and implementation of the intelligent navigation algorithms, which is capable of navigating a mobile robot autonomously in static as well as dynamic environments. Navigation and obstacle avoidance are one of the most important tasks for any mobile robots. The primary objective of this research work is to improve the navigation accuracy and efficiency of the mobile robot using various soft computing techniques. In this research work, Hybrid Fuzzy (H-Fuzzy) architecture, Cascade Neuro-Fuzzy (CN-Fuzzy) architecture, Fuzzy-Simulated Annealing (Fuzzy-SA) algorithm, Wind Driven Optimization (WDO) algorithm, and Fuzzy-Wind Driven Optimization (Fuzzy-WDO) algorithm have been designed and implemented to solve the navigation problems of a mobile robot in different static and dynamic environments. The performances of these proposed techniques are demonstrated through computer simulations using MATLAB software and implemented in real time by using experimental mobile robots. Furthermore, the performances of Wind Driven Optimization algorithm and Fuzzy-Wind Driven Optimization algorithm are found to be most efficient (in terms of path length and navigation time) as compared to rest of the techniques, which verifies the effectiveness and efficiency of these newly built techniques for mobile robot navigation. The results obtained from the proposed techniques are compared with other developed techniques such as Fuzzy Logics, Genetic algorithm (GA), Neural Network, and Particle Swarm Optimization (PSO) algorithm, etc. to prove the authenticity of the proposed developed techniques