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Water Sink Model for Robot Motion Planning.

Gi-Yoon Jeon1,2, Jin-Woo Jung3

  • 1Department of Computer Science and Engineering, Dongguk University, 30, Pildong-Ro 1-Gil, Jung-Gu, Seoul 04620, Korea. gyjeon@add.re.kr.

Sensors (Basel, Switzerland)
|March 16, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a novel water sink model to solve the local minima problem in robot motion planning. This method ensures robots can always reach their goal, overcoming limitations of potential field techniques.

Keywords:
artificial potential fieldlocal minimarobot motion planningwater sink model

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Area of Science:

  • Robotics and Artificial Intelligence
  • Computational Geometry
  • Control Systems

Background:

  • Robot motion planning is crucial for autonomous systems.
  • Potential field methods offer smooth paths but suffer from local minima.
  • Existing solutions for local minima are insufficient.

Purpose of the Study:

  • To propose a novel water sink model for robot motion planning.
  • To overcome the local minima problem inherent in potential field methods.
  • To provide a robust and reliable goal-reaching mechanism for agents.

Main Methods:

  • Development of a water sink model simulating water flow towards a plughole (goal).
  • Implementation of a water sink model simulator.
  • Comparative experimental analysis against traditional potential field methods.

Main Results:

  • The water sink model effectively guides the robot towards the goal.
  • The proposed method successfully avoids or overcomes local minima.
  • Experimental results demonstrate the efficacy of the water sink model.

Conclusions:

  • The water sink model presents a viable solution to the local minima problem in motion planning.
  • This approach offers a more reliable alternative to existing potential field methods.
  • The water sink model ensures consistent goal achievement for robots.