Enhanced path smoothing based on conjugate gradient descent for firefighting robots in petrochemical complexes*

Naoki Mizuno, Kazunori Ohno, Ryunosuke Hamada, Hiroyoshi Kojima, Jun Fujita, Hisanori Amano, Thomas Westfechtel, Takahiro Suzuki, Satoshi Tadokoro

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


The firefighting robot system (FFRS) comprises several autonomous robots that can be deployed to fire disasters in petrochemical complexes. For autonomous navigation, the path planner should consider the robot constraints and characteristics. Specifically, three requirements should be satisfied for a path to be suitable for the FFRS. First, the path must satisfy the maximum curvature constraint. Second, it must be smooth for robots to easily execute the trajectory. Third, it must allow reaching the target location in a specific heading. We propose a path planner that provides smooth paths, satisfy the maximum curvature constraint, and allows a suitable robot heading. The path smoother is based on the conjugate gradient descent, and three approaches are proposed for this path planner to meet all the FFRS requirements. The effectiveness of these approaches is qualitatively and quantitatively evaluated by examining the generated paths. Finally, the path planner is applied to an actual robot to verify the suitability of the generated paths for the FFRS, and planning is applied to another type of robot to demonstrate the wide applicability of the proposed planner.

Original languageEnglish
Pages (from-to)687-698
Number of pages12
JournalAdvanced Robotics
Issue number14
Publication statusPublished - 2019 Jul 18


  • autonomous ground vehicle
  • firefighting robot
  • mobile robot
  • motion planning
  • Path smoothing


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