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GA Algorithms in Intelligent Robots

In: Fuzzy Evolutionary Computation

Author

Listed:
  • Toshio Fukuda

    (Nagoya University, Department of Micro System Enginering)

  • Naoyuki Kubota

    (Nagoya University, Department of Micro System Enginering)

  • Takemasa Arakawa

    (Nagoya University, Department of Micro System Enginering)

Abstract

This chapter presents the role of genetic algorithms in intelligent robots. In general, the motion planning problems in intelligent robots can be fundamentally split into path planning problems, trajectory planning problems, and task planning problems. These planning faculties have many constraints concerning kinematics and dynamics of the robot and therefore it is very difficult to solve these planning problems. This chapter presents the general application of genetic algorithms to these planning tasks. Furthermore, the chapter discusses a trajectory planning problem for redundant manipulators and a motion planning problem for biped locomotion robots.

Suggested Citation

  • Toshio Fukuda & Naoyuki Kubota & Takemasa Arakawa, 1997. "GA Algorithms in Intelligent Robots," Springer Books, in: Witold Pedrycz (ed.), Fuzzy Evolutionary Computation, chapter 2, pages 81-105, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4615-6135-4_4
    DOI: 10.1007/978-1-4615-6135-4_4
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