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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Mobile robots are increasingly used in tasks like surveillance and search and rescue.
  • Efficient and safe navigation in dynamic environments is crucial for robot applications.
  • Existing methods may struggle with replanning and smooth trajectory generation.

Purpose of the Study:

  • To propose an online smooth-motion-planning method for mobile robots.
  • To generate collision-free patrolling trajectories using clothoid curves.
  • To improve navigation efficiency and safety in dynamic environments.

Main Methods:

  • Developed an online smooth-motion-planning method based on clothoid curves.
  • Combined global and local planning strategies for adaptability in large, changing environments.
  • Integrated a golden ratio-based path smoothing technique for obstacle avoidance and orientation alignment.

Main Results:

  • The proposed algorithm significantly reduced patrolling execution time and path length.
  • Demonstrated reduced deviation of the tracked trajectory from the planned route.
  • Validated real-time operational capability and performance with a differential-drive mobile robot.

Conclusions:

  • The novel method enables smoother, more efficient, and safer mobile robot patrolling.
  • The algorithm is computationally simple, suitable for real-time applications.
  • Clothoid curve-based planning offers advantages for dynamic environment navigation.