Dynamic path planning of mobile robots based on ABC algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6320 LNAI, Issue PART 2, 2010, Pages 267-274

  Ma, Qianzhi ^a   Lei, Xiujuan ^a  

^a SHAANXI NORMAL UNIVERSITY   (China)

Author keywords

Artificial bee colony algorithm; dynamic path planning; Mobile robot

Indexed keywords

ARTIFICIAL BEE COLONIES; DYNAMIC PATH PLANNING; DYNAMIC UNCERTAIN ENVIRONMENTS; FITNESS FUNCTIONS; GLOBAL PATH PLANNING; PATH PLANNING METHOD; RAPID CONVERGENCE; REAL TIME REQUIREMENT; ROLLING WINDOW; SIMULATION RESULT;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CONVERGENCE OF NUMERICAL METHODS; FLIGHT DYNAMICS; FUNCTION EVALUATION; GLOBAL OPTIMIZATION; MOBILE ROBOTS;

ROBOT PROGRAMMING;

EID: 78649978041     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16527-6_34     Document Type: Conference Paper

References (7)

1. Ge, S.S., Cui, Y.J.: New Potential Functions for Mobile Robot Path Planning. IEEE Transactions on Robotics and Automation (May 2000)
2. Huang, H., Chung, S.: Dynamic visibility graph for path planning. In: Intelligent Robots and Systems, 2004, pp. 2813-2818. IEEE, Sendai (2004)
3. Sadati, N., Taheri, J.: Genetic algorithm in robot path planning problem in crisp and fuzzified environments. In: Proceedings of IEEE International Conference on Industrial Technology, vol. (1), pp. 11-14. IEEE, Bangkok (2002)
4. Basturk, B., Karaboga, D.: An Artificial Bee Colony(ABC) Algorithm for Numeric function Optimization. In: IEEE Swarm Intelligence Symposium 2006, USA (2006)
5. Singh, A.: An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem. Applied Soft Computing 9(2), 625-631 (2009)
6. Sipahioglu, A., Yazicib, A. (eds.): Real-time tour construction for a mobile robot in a dynamic environment. Robotics and Autonomous Systems (56), 289-295 (2008)
7. Cai, X., Li, Y., Wu, T.: Dynamic Path Planning of Mobile Robots in Uncertain Environments Based on PSO and Receding Horizon Optimization. Bulletin of science and technology 24(2), 260-265 (2008)