No abstract

No abstract

No abstract

Purpose This paper aims to propose an optimized overview of firefly algorithm (FA) over physical-natural impression of fireflies and its application in mobile robot navigation under the natural intelligence mechanism. Design/methodology/approach The brightness and luminosity are the decision variables in proposed study. The paper achieves the two major goals of robot navigation; first, the optimum path generation and, second, as an obstacle avoidance by co-in-centric sphere-based geometrical technique. This technique comprises the optimum path decision to objective function and constraints to paths and obstacles as the function of algebraic-geometry co-relation. Co-in-centric sphere is the proposed technique to correlate the constraints. Findings It is found that the present FA based on concentric sphere is suitable for efficient navigation of mobile robots at the level of optimum significance when compared with other approaches. Originality/value The paper introduces a novel approach to implement the FA for unknown and uncertain environment.

Purpose This paper aims to design and implement the multiple adaptive neuro-fuzzy inference system (MANFIS) architecture-based sensor-actuator (motor) control technique for mobile robot navigation in different two-dimensional environments with the presence of static and moving obstacles. Design/methodology/approach The three infrared range sensors have been mounted on the front, left and right side of the robot, which reads the forward, left forward and right forward static and dynamic obstacles in the environment. This sensor data information is fed as inputs into the MANFIS architecture to generate appropriate speed control commands for right and left motors of the robot. In this study, we have taken one assumption for moving obstacle avoidance in different scenarios the speed of the mobile robot is at least greater than or equal to the speed of moving obstacles and goal. Findings Graphical simulations have designed through MATLAB and virtual robot experimentation platform (V-REP) software and experiments have been done on Arduino MEGA 2560 microcontroller-based mobile robot. Simulation and experimental studies demonstrate the effectiveness and efficiency of the proposed MANFIS architecture. Originality/value This paper designs and implements MANFIS architecture for mobile robot navigation between a static and moving obstacle in different simulation and experimental environments. Also, the authors have compared this developed architecture to the other navigational technique and found that our developed architecture provided better results in terms of path length in the same environment.

The frequency, deflection, and stress values of carbon nanotube reinforced sandwich plate structure is investigated numerically under the influence of the mechanical loading and thermal field. The effective properties of individual components of sandwich structure (face sheet and core layer) are assumed to be temperature‐dependent and modeled via thermoelastic constitutive relations. In addition, the distribution of carbon nanotube through the thickness of the face sheets are assumed to follow the rule based grading pattern. Further, the sandwich structural panel modeled using the extant high‐order shear deformation kinematic theory for the mathematical purpose. The desired structural responses (frequency, deflection and stress) obtained numerically through a generic finite element based computer code developed in MATLAB. The convergence criteria and the accuracy of the current high‐order finite element solutions have been assessed by solving a sufficient number of numerical examples. Lastly, the influences of structural parameters (core to face thickness ratios, carbon nanotube fractions, type of loading, aspect ratios, end constraints, length to thickness ratios, type of carbon nanotube gradings, and type of temperature gradings) on the transverse deflection and frequencies of carbon nanotube‐reinforced sandwich structure are obtained under the elevated thermal field and the subsequent conclusions discussed accordingly. POLYM. COMPOS., 39:3792–3809, 2018. © 2017 Society of Plastics Engineers

No abstract

No abstract