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Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
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A novel RRT*-Connect algorithm for path planning on robotic arm collision avoidance.

Miaolong Cao1, Huawei Mao2, Xiaohui Tang3

  • 1School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023, China. cml_q@163.com.

Scientific Reports
|January 22, 2025
PubMed
Summary
This summary is machine-generated.

An improved RRT*-Connect algorithm enhances robotic arm path planning for obstacle avoidance. This optimized algorithm reduces run time and path length, ensuring efficient and safe navigation.

Keywords:
Path planningRRT algorithmRobotic armSampling-based algorithms

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Motion Planning

Background:

  • Original RRT*-Connect algorithm has limitations in path planning efficiency.
  • Robotic arm navigation requires optimal obstacle avoidance strategies.

Purpose of the Study:

  • To present an original RRT*-Connect algorithm for robotic arm obstacle avoidance path planning.
  • To enhance path planning efficiency and optimality through various optimization techniques.

Main Methods:

  • Implemented target biasing and elliptic space sampling for improved sampling.
  • Revised cost function and incorporated artificial potential field with gradient descent for adaptive step sizes.
  • Utilized segmented Bézier curves for smoother trajectory generation.

Main Results:

  • Simulations demonstrated a 19.39% reduction in average run time.
  • Simulations showed a 5% reduction in average path length compared to the original algorithm.
  • Experimental verification confirmed the algorithm's effectiveness on a robotic arm.

Conclusions:

  • The enhanced RRT*-Connect algorithm provides optimal obstacle avoidance path planning.
  • The algorithm consistently finds shorter paths while effectively avoiding obstacles.
  • Proposed strategies successfully address limitations of the original algorithm for practical robotic applications.