A unified motion planning method for a multifunctional underwater robot

Koichiro Shiraishi, Hajime Kimura

Research output: Contribution to journalArticlepeer-review


This article deals with motion planning for a multifunctional underwater robot that can perform various tasks such as swimming, walking, and grasping objects. We have developed a unified motion planning method that can generate motion planning for a variety of movements using a single algorithm. With this method, motion planning problems are modeled as finite-horizon Markov decision processes, and optimum motion planning is achieved by dynamic programming. However, conventional dynamic programming is sometimes considered to have limited applicability because of "the curse of dimensionality." To avoid this issue, we applied a random network as a state transition network to suppress the explosion in the number of states. The effectiveness of the proposed method is demonstrated through numerical simulations involving two types of task for multifunctional robots. One is a reaching task, and the other is a thrust force generation task.

Original languageEnglish
Pages (from-to)405-409
Number of pages5
JournalArtificial Life and Robotics
Issue number3
Publication statusPublished - Dec 2009

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence


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