Robot Path Planning Using Improved Artificial Bee Colony Algorithm

By analyzing the research status of artificial bee colony algorithm and robot path planning, an improved artificial bee colony algorithm is proposed in this paper. Firstly, this paper elaborates the robot movement map environment modeling. Secondly, the robot path planning problem is transformed into a mathematical modeling problem, and the robot path planning is mathematically modeled. Thirdly, through the analysis of the robot planning of the traditional artificial bee colony algorithm, the concept of physical strength of bees was introduced. Fourthly, an improved artificial bee colony algorithm based on bee physical strength was proposed to accelerate the algorithm convergence and find the global optimal path. Finally, the artificial bee colony algorithm based on bee physical strength was simulated in the robot path planning method. By comparing the results of the two algorithms in path planning, the feasibility and effectiveness of algorithm proposed by the paper are verified.

[1]  Fred Rothganger,et al.  An implemented planner for manipulating a polygonal object in the plane with three disc-shaped mobile robots , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[2]  Parham Moradi,et al.  Velocity based artificial bee colony algorithm for high dimensional continuous optimization problems , 2014, Eng. Appl. Artif. Intell..

[3]  Calin Belta,et al.  Optimality and Robustness in Multi-Robot Path Planning with Temporal Logic Constraints , 2013, Int. J. Robotics Res..

[4]  Lorenzo Sciavicco,et al.  The parallel approach to force/position control of robotic manipulators , 1993, IEEE Trans. Robotics Autom..

[5]  Hao Zhang,et al.  A hybrid multi-objective artificial bee colony algorithm for burdening optimization of copper strip production , 2012 .

[6]  Mesut Gündüz,et al.  The Analysis of Peculiar Control Parameters of Artificial Bee Colony Algorithm on the Numerical Optimization Problems , 2014 .

[7]  Jong-Hwan Kim,et al.  A real-time limit-cycle navigation method for fast mobile robots and its application to robot soccer , 2003, Robotics Auton. Syst..

[8]  Anders Orebäck,et al.  Evaluation of Architectures for Mobile Robotics , 2003, Auton. Robots.

[9]  Keiji Nagatani,et al.  Path and sensing point planning for mobile robot navigation to minimize the risk of collision , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[10]  Anastasios I. Dounis,et al.  Artificial intelligence for energy conservation in buildings , 2010 .

[11]  Gerardo Schneider,et al.  A framework for conflict analysis of normative texts written in controlled natural language , 2013, J. Log. Algebraic Methods Program..

[12]  Magnus Egerstedt,et al.  Autonomous driving in urban environments: approaches, lessons and challenges , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[13]  Tianjun Liao,et al.  Artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch problem , 2014 .