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Performance Improvement of RRT* Family Algorithms by Limiting Sampling Range in Circular and Spherical Obstacle Environments

샘플링 범위 제한을 이용한 원 및 구 장애물 환경에서의 RRT* 계열 알고리즘 성능 개량

  • Lee, Sangil (Department of Military Digital Convergence, Ajou University) ;
  • Park, Jongho (Department of Military Digital Convergence, Ajou University) ;
  • Lim, Jaesung (Department of Military Digital Convergence, Ajou University)
  • Received : 2021.11.24
  • Accepted : 2022.10.18
  • Published : 2022.11.01

Abstract

The development of unmanned robots and UAVs has increased the need for path planning methods such as RRT* algorithm. It mostly works well in various environments and is utilized in many fields. A lot of research has been conducted to obtain a better path in terms of efficiency through various modifications to the RRT* algorithm, and the performance of the algorithm is continuously improved thanks to these efforts. In this study, a method using the limitation of sampling range is proposed as an extension of these efforts. Based on the idea that a path passing close to obstacles is similar to the optimal path in obstacle environments, nodes are produced around the obstacle. Also, rewiring algorithm is modified to quickly obtain the path. The performance of the proposed algorithm is validated by comparative analysis of the previous basic algorithm and the generated path is tracked by a UAV's kinematic model for further verification.

무인 로봇과 UAV의 발달로 경로 계획 알고리즘의 필요성이 높아지고 있으며 다양한 환경에서 잘 작동하는 RRT* 알고리즘이 여러 분야에서 유용하게 활용되고 있다. RRT* 알고리즘에 다양한 변형을 통해 더 좋은 경로를 생성하기 위한 많은 연구가 진행되고 있으며, 이러한 노력 덕분에 알고리즘의 성능 향상은 거듭되는 중이다. 본 논문은 이러한 연구의 연장선에서 샘플링 범위의 제한을 이용하여 효율적인 경로를 생성하는 방법을 제안한다. 장애물이 있는 환경에서 경로가 장애물에 근접할수록 최적의 경로에 가까워진다는 발상에 근거하여 더 짧은 경로를 얻기 위해 장애물 근처에 노드를 생성한다. 또한 경로가 장애물을 휘감는 경우 변경된 재연결 방법을 통해 빠르게 직선화된 경로를 얻는다. 기존의 알고리즘과 제안하는 방법을 비교 분석하여 성능을 검증하고, 무인항공기의 운동학 모델을 도입하여 생성된 경로를 추적할 수 있음을 확인한다.

Keywords

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