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Improved A* Algorithm for Path Planning of Spherical Robot Considering Energy Consumption.

Hao Ge1, Zhanfeng Ying2, Zhihua Chen1

  • 1National Key Laboratory of Transient Physics, Nanjing University of Science & Technology, Nanjing 210094, China.

Sensors (Basel, Switzerland)
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Summary

This study introduces an improved A* algorithm for spherical robots, optimizing path planning by minimizing both energy consumption and path length. This novel approach enhances navigation efficiency on complex terrains.

Keywords:
energy consumptionimproved A-star algorithmpath planningspherical robot

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Path Planning

Background:

  • Spherical robots possess fully wrapped shells, enabling effective locomotion on diverse and complex terrains like swamps, grasslands, and deserts.
  • Current path planning algorithms for spherical robots primarily focus on identifying the shortest path, often neglecting energy efficiency.

Purpose of the Study:

  • To propose an improved A* algorithm for spherical robot path planning that considers and minimizes energy consumption alongside path length.
  • To enhance the navigation capabilities of spherical robots by optimizing for both distance and energy usage.

Main Methods:

  • An improved A* algorithm was developed, incorporating an energy consumption estimation model (ECEM) and a distance estimation model (DEM) into its heuristic function.
  • The ECEM was established through force analysis of the spherical robot, while the DEM utilized an improved Euclidean distance metric for grid maps.
  • Simulations were conducted using a 3D grid map and a uniformly moving spherical robot to validate the algorithm's effectiveness.

Main Results:

  • The proposed algorithm successfully minimized both the energy consumption and path length for the spherical robot.
  • Comparative analysis demonstrated that the improved A* algorithm outperforms traditional path planning methods in optimizing for energy and distance.

Conclusions:

  • The developed heuristic function effectively balances energy consumption and path length objectives.
  • The improved A* algorithm offers a more efficient and optimized path planning solution for spherical robots operating in complex environments.