Path planning in uncertain environment by using firefly algorithm

Abstract Autonomous mobile robot navigation is one of the most emerging areas of research by using swarm intelligence. Path planning and obstacle avoidance are most researched current topics like navigational challenges for mobile robot. The paper presents application and implementation of Firefly Algorithm (FA) for Mobile Robot Navigation (MRN) in uncertain environment. The uncertainty is defined over the changing environmental condition from static to dynamic. The attraction of one firefly towards the other firefly due to variation of their brightness is the key concept of the proposed study. The proposed controller efficiently explores the environment and improves the global search in less number of iterations and hence it can be easily implemented for real time obstacle avoidance especially for dynamic environment. It solves the challenges of navigation, minimizes the computational calculations, and avoids random moving of fireflies. The performance of proposed controller is better in terms of path optimality when compared to other intelligent navigational approaches.

[1]  Michael Brand,et al.  Autonomous robot path optimization using firefly algorithm , 2013, 2013 International Conference on Machine Learning and Cybernetics.

[2]  Sunil Kumar Kashyap,et al.  Matrix-Binary Codes based Genetic Algorithm for path planning of mobile robot , 2017, Comput. Electr. Eng..

[3]  Danica Janglova,et al.  Neural Networks in Mobile Robot Motion , 2004, ArXiv.

[4]  O. P. Sahu,et al.  Real Time Navigation Approach for Mobile Robot , 2017, J. Comput..

[5]  Rahul Kala,et al.  MULTIROBOT MOTION PLANNING USING HYBRID MNHS AND GENETIC ALGORITHMS , 2013, Appl. Artif. Intell..

[6]  Miguel A. Vega-Rodríguez,et al.  Solving the multi-objective path planning problem in mobile robotics with a firefly-based approach , 2015, Soft Computing.

[7]  Qidi Wu,et al.  A fast two-stage ACO algorithm for robotic path planning , 2011, Neural Computing and Applications.

[8]  Mukesh A. Zaveri,et al.  Reactive Navigation of Autonomous Mobile Robot Using Neuro- Fuzzy System , 2011 .

[9]  Jianhua Zhang,et al.  Robot path planning in uncertain environment using multi-objective particle swarm optimization , 2013, Neurocomputing.

[10]  Jianguo Wang,et al.  Adaptive Genetic Algorithm Enhancements for Path Planning of Mobile Robots , 2010, 2010 International Conference on Measuring Technology and Mechatronics Automation.

[11]  Hanning Chen,et al.  Mobile robot path planning based on adaptive bacterial foraging algorithm , 2013 .

[12]  Zoran Miljkovic,et al.  Bio-inspired approach to learning robot motion trajectories and visual control commands , 2015, Expert Syst. Appl..

[13]  K. Wood,et al.  Firefly luciferase gene: structure and expression in mammalian cells , 1987, Molecular and cellular biology.

[14]  Feng Gao,et al.  Three-Dimensional Path Planning Method for Autonomous Underwater Vehicle Based on Modified Firefly Algorithm , 2015 .

[15]  Iztok Fister,et al.  Memetic firefly algorithm for combinatorial optimization , 2012, 1204.5165.

[16]  Sunil Kumar Kashyap,et al.  On firefly algorithm: optimization and application in mobile robot navigation , 2017 .

[17]  Gai-Ge Wang,et al.  A modified firefly algorithm for UCAV path planning , 2012 .

[18]  Yu-Chu Tian,et al.  Dynamic robot path planning using an enhanced simulated annealing approach , 2013, Appl. Math. Comput..

[19]  Weiren Shi,et al.  A Fuzzy-Neural Network Approach To Multisensor Integration For Obstacle Avoidance Of A Mobile Robot , 2009, Intell. Autom. Soft Comput..

[20]  Amit Konar,et al.  Synergism of Firefly Algorithm and Q-Learning for Robot Arm Path Planning , 2018, Swarm Evol. Comput..

[21]  Cyril Fonlupt,et al.  A set of new compact firefly algorithms , 2017, Swarm Evol. Comput..

[22]  Dayal R. Parhi,et al.  Optimal path planning for a mobile robot using cuckoo search algorithm , 2016, J. Exp. Theor. Artif. Intell..

[23]  Anish Pandey,et al.  Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm , 2017 .

[24]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[25]  Ching-Hung Lee,et al.  Efficient collision-free path-planning of multiple mobile robots system using efficient artificial bee colony algorithm , 2015, Adv. Eng. Softw..