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

Cooperation of Multiple Fish-like Microrobots Based on Reinforcement Learning

Abstract-This paper is concerned with cooperative control of a kind of multiple fish-like microrobots. Most of previous work on multi-robot cooperation is focused on the terrestrial robots and seldom deals with underwater applications. In fact, the tasks in hydro-environment is more challenging than those in ground circumstances and need the cooperation of robots much more. In this paper, we investigate this problem in the framework of an adversarial game with several underwater microrobots. A fuzzy reinforcement learning approach is adopted to acquire cooperative behavior and a behavioral hierarchical architecture is proposed. We conduct extensive experiments to verify the effectiveness of the proposed algorithms

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

DAQL-Enabled Autonomous Vehicle Navigation in Dynamically Changing Environment

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Advanced Techniques for Design and Manufacturing in Marine Engineering

Modern engineering design processes are driven by the extensive use of numerical simulations; naval architecture and ocean engineering are no exception. Computational power has been improved over the last few decades; therefore, the integration of different tools such as CAD, FEM, CFD, and CAM has enabled complex modeling and manufacturing problems to be solved in a more feasible way. Classical naval design methodology can take advantage of this integration, giving rise to more robust designs in terms of shape, structural and hydrodynamic performances, and the manufacturing process.This Special Issue invites researchers and engineers from both academia and the industry to publish the latest progress in design and manufacturing techniques in marine engineering and to debate the current issues and future perspectives in this research area. Suitable topics for this issue include, but are not limited to, the following:CAD-based approaches for designing the hull and appendages of sailing and engine-powered boats and comparisons with traditional techniques;Finite element method applications to predict the structural performance of the whole boat or of a portion of it, with particular attention to the modeling of the material used;Embedded measurement systems for structural health monitoring;Determination of hydrodynamic efficiency using experimental, numerical, or semi-empiric methods for displacement and planning hulls;Topology optimization techniques to overcome traditional scantling criteria based on international standards;Applications of additive manufacturing to derive innovative shapes for internal reinforcements or sandwich hull structures

Navigation Techniques for Control of Multiple Mobile Robots

The investigation reported in this thesis attempt to develop efficient techniques for the control of multiple mobile robots in an unknown environment. Mobile robots are key components in industrial automation, service provision, and unmanned space exploration. This thesis addresses eight different techniques for the navigation of multiple mobile robots. These are fuzzy logic, neural network, neuro-fuzzy, rule-base, rule-based-neuro-fuzzy, potential field, potential-field-neuro-fuzzy, and simulated-annealing- potential-field- neuro-fuzzy techniques. The main components of this thesis comprises of eight chapters. Following the literature survey in Chapter-2, Chapter-3 describes how to calculate the heading angle for the mobile robots in terms of left wheel velocity and right wheel velocity of the robot. In Chapter-4 a fuzzy logic technique has been analysed. The fuzzy logic technique uses different membership functions for navigation of the multiple mobile robots, which can perform obs..

Analysis and Development of Computational Intelligence based Navigational Controllers for Multiple Mobile Robots

Navigational path planning problems of the mobile robots have received considerable attention over the past few decades. The navigation problem of mobile robots are consisting of following three aspects i.e. locomotion, path planning and map building. Based on these three aspects path planning algorithm for a mobile robot is formulated, which is capable of finding an optimal collision free path from the start point to the target point in a given environment. The main objective of the dissertation is to investigate the advanced methodologies for both single and multiple mobile robots navigation in highly cluttered environments using computational intelligence approach. Firstly, three different standalone computational intelligence approaches based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), Cuckoo Search (CS) algorithm and Invasive Weed Optimization (IWO) are presented to address the problem of path planning in unknown environments. Next two different hybrid approaches are developed using CS-ANFIS and IWO-ANFIS to solve the mobile robot navigation problems. The performance of each intelligent navigational controller is demonstrated through simulation results using MATLAB. Experimental results are conducted in the laboratory, using real mobile robots to validate the versatility and effectiveness of the proposed navigation techniques. Comparison studies show, that there are good agreement between them. During the analysis of results, it is noticed that CS-ANFIS and IWO-ANFIS hybrid navigational controllers perform better compared to other discussed navigational controllers. The results obtained from the proposed navigation techniques are validated by comparison with the results from other intelligent techniques such as Fuzzy logic, Neural Network, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and other hybrid algorithms. By investigating the results, finally it is concluded that the proposed navigational methodologies are efficient and robust in the sense, that they can be effectively implemented to solve the path optimization problems of mobile robot in any complex environment