On firefly algorithm: optimization and application in mobile robot navigation

2017 ◽  
Vol 14 (1) ◽  
pp. 65-76 ◽  
Author(s):  
B.K. Patle ◽  
Dayal R. Parhi ◽  
A. Jagadeesh ◽  
Sunil Kumar Kashyap
Keyword(s):  
Mobile Robot ◽  
Design Methodology ◽  
Firefly Algorithm ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Algorithm Optimization ◽  
Content Type ◽  
Novel Approach ◽  
Decision Variables ◽  
Optimum Path

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.

scholarly journals PSO based path planner of an autonomous mobile robot

2012 ◽  
Vol 2 (2) ◽  
Author(s):  
B. Deepak ◽  
Dayal Parhi
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Fitness Function ◽  
Optimal Path ◽  
Mobile Robot Navigation ◽  
Autonomous Mobile Robot ◽  
Swarm Optimization ◽  
Novel Approach ◽  
Fitness Value ◽  
Path Planner

AbstractA novel approach based on particle swarm optimization has been presented in this paper for solving mobile robot navigation task. The proposed technique tries to optimize the path generated by an intelligent mobile robot from its source position to destination position in its work space. For solving this problem, a new fitness function has been modelled, which satisfies the obstacle avoidance and optimal path traversal conditions. From the obtained fitness values of each particle in the swarm, the robot moves towards the particle which is having optimal fitness value. Simulation results are provided to validate the feasibility of the developed methodology in various unknown environments.

Autonomous mobile robot navigation between static and dynamic obstacles using multiple ANFIS architecture

2019 ◽  
Vol 16 (2) ◽  
pp. 275-286 ◽  
Author(s):  
Anish Pandey ◽  
Abhishek Kumar Kashyap ◽  
Dayal R. Parhi ◽  
B.K. Patle
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Experimental Studies ◽  
Sensor Data ◽  
Mobile Robot Navigation ◽  
Control Technique ◽  
Inference System ◽  
Content Type ◽  
Moving Obstacles ◽  
Moving Obstacle

PurposeThis 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/approachThe 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.FindingsGraphical 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/valueThis 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.

Goal-directed affordance prediction at the subtask level

2016 ◽  
Vol 43 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Huaqing Min ◽  
Chang'an Yi ◽  
Ronghua Luo ◽  
Jinhui Zhu
Keyword(s):  
Mobile Robot ◽  
Hybrid Control ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Control Architecture ◽  
Autonomous Mobile Robot ◽  
Reactive Control ◽  
Navigation Task ◽  
Content Type ◽  
Hybrid Control Architecture

Purpose – This paper aims to present a hybrid control approach that combines learning-based reactive control and affordance-based deliberate control for autonomous mobile robot navigation. Unlike many current navigation approaches which only use learning-based paradigms, the authors focus on how to utilize the machine learning methods for reactive control together with the affordance knowledge that is simultaneously inherent in natural environments to gain advantages from both local and global optimization. Design/methodology/approach – The idea is to decompose the complex and large-scale robot navigation task into multiple sub-tasks and use the hierarchical reinforcement learning (HRL) algorithm, which is well-studied in the learning and control algorithm domains, to decompose the overall task into sub-tasks and learn a grid-topological map of the environment. An affordance-based deliberate controller is used to inspect the affordance knowledge of the obstacles in the environment. The hybrid control architecture is then designed to integrate the learning-based reactive control and affordance-based deliberate control based on the grid-topological and affordance knowledge. Findings – Experiments with computer simulation and an actual humanoid NAO robot have demonstrated the effectiveness of the proposed hybrid approach for mobile robot navigation. Originality/value – The main contributions of this paper are a new robot navigation framework that decomposes a complex navigation task into multiple sub-tasks using the HRL approach, and hybrid control architecture development that integrates learning-based and affordance-based paradigms for autonomous mobile robot navigation.

Autonomous mobile robot navigation in cluttered environment using hybrid Takagi-Sugeno fuzzy model and simulated annealing algorithm controller

2016 ◽  
Vol 13 (5) ◽  
pp. 431-440 ◽  
Author(s):  
Anish Pandey ◽  
Dayal R. Parhi
Keyword(s):  
Simulated Annealing ◽  
Mobile Robot ◽  
Hybrid Algorithm ◽  
Robot Navigation ◽  
Fuzzy Model ◽  
Mobile Robot Navigation ◽  
Content Type ◽  
Cluttered Environment ◽  
Control Command ◽  
Takagi Sugeno

Purpose This paper aims to design a Takagi–Sugeno fuzzy model with a simulated annealing hybrid algorithm (fuzzy-SAA) that was implemented for mobile robot navigation and obstacle avoidance in a cluttered environment. Design/methodology/approach The SAA is used to optimize the output parameters of the fuzzy controller. The ultrasonic range finder sensor and sharp infrared range sensor are used for calculating the different obstacle distances, such as front, right and left obstacle distance, for selecting the suitable steering angle control command in the environment. Findings The simulation and experimental results show the proposed method is feasible and valid for a wheeled mobile robot moving in a cluttered environment. Originality/value The developed fuzzy-SAA hybrid algorithm provides better results (in terms of navigation path length and time) as compared to previous works, which verifies the effectiveness and efficiency of the developed hybrid algorithm.

A Novel Approach for Mobile Robot Navigation with Dynamic Obstacles Avoidance

2005 ◽  
Vol 44 (3) ◽  
pp. 187-201 ◽  
Author(s):  
Salim Belkhous ◽  
Adel Azzouz ◽  
Maarouf Saad ◽  
Chahé Nerguizian ◽  
Vahé Nerguizian
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Novel Approach

DEVELOPMENT OF A CONTROL STRATEGY FOR MOBILE ROBOT NAVIGATION IN UNKNOWN TERRAIN

2019 ◽  
Author(s):  
Diego Gabriel Gomes Rosa ◽  
Carlos Luiz Machado de souza junior ◽  
Marco Antonio Meggiolaro ◽  
Luiz Fernando Martha
Keyword(s):  
Mobile Robot ◽  
Control Strategy ◽  
Robot Navigation ◽  
Mobile Robot Navigation

Real-time road edge following for mobile robot navigation

1990 ◽  
Vol 2 (1) ◽  
pp. 35 ◽  
Author(s):  
R.A. Lotufo ◽  
A.D. Morgan ◽  
E.L. Dagless ◽  
D.J. Milford ◽  
J.F. Morrissey ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Robot Navigation ◽  
Mobile Robot Navigation

scholarly journals Path Planning and Replanning for Mobile Robot Navigation on 3D Terrain: An Approach Based on Geodesic

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Kun-Lin Wu ◽  
Ting-Jui Ho ◽  
Sean A. Huang ◽  
Kuo-Hui Lin ◽  
Yueh-Chen Lin ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Tangent Plane ◽  
Intersection Point ◽  
Mobile Robot Navigation ◽  
Complete Manifold ◽  
Geodesic Triangle ◽  
Planning Stage ◽  
3D Terrain ◽  
Bonnet Theorem

In this paper, mobile robot navigation on a 3D terrain with a single obstacle is addressed. The terrain is modelled as a smooth, complete manifold with well-defined tangent planes and the hazardous region is modelled as an enclosing circle with a hazard grade tuned radius representing the obstacle projected onto the terrain to allow efficient path-obstacle intersection checking. To resolve the intersections along the initial geodesic, by resorting to the geodesic ideas from differential geometry on surfaces and manifolds, we present a geodesic-based planning and replanning algorithm as a new method for obstacle avoidance on a 3D terrain without using boundary following on the obstacle surface. The replanning algorithm generates two new paths, each a composition of two geodesics, connected via critical points whose locations are found to be heavily relying on the exploration of the terrain via directional scanning on the tangent plane at the first intersection point of the initial geodesic with the circle. An advantage of this geodesic path replanning procedure is that traversability of terrain on which the detour path traverses could be explored based on the local Gauss-Bonnet Theorem of the geodesic triangle at the planning stage. A simulation demonstrates the practicality of the analytical geodesic replanning procedure for navigating a constant speed point robot on a 3D hill-like terrain.

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