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A Comprehensive Obstacle Avoidance System of Mobile Robots Using an Adaptive Threshold Clustering and the Morphin Algorithm

  • Meng Yuan Chen
  • Yong Jian Wu
  • Hongmei He
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 840)

Abstract

To solve the problem of obstacle avoidance for a mobile robot in unknown environment, a comprehensive obstacle avoidance system (called ATCM system) is developed. It integrates obstacle detection, obstacle classification, collision prediction and obstacle avoidance. Especially, an Adaptive-Threshold Clustering algorithm is developed to detect obstacles, and the Morphin algorithm is applied for path planning when the robot predicts a collision ahead. A dynamic circular window is set to continuously scan the surrounding environment of the robot during the task period. The simulation results show that the obstacle avoidance system enables robot to avoid any static and dynamic obstacles effectively.

Keywords

Adaptive threshold clustering Morphin algorithm Obstacle detection Obstacle classification Collision prediction Collision avoidance 

Notes

Acknowledgments

This work was supported by 2018 Natural Science Foundation of Anhui, China (1808085QF215), 2018 Foundation for Distinguished Young Talents in Higher Education of Anhui, China (gxyqZD2018050) and Anhui Key Research and Development Programs (Foreign Scientific and Technological Cooperation, 1804b06020375).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Key Lab of Electric Drive and Control of Anhui ProvinceAnhui Polytechnic UniversityWuhuChina
  2. 2.Department of Precision Machinery and Precision InstrumentationUniversity of Science and Technology of ChinaHefeiChina
  3. 3.Manufacturing Informatics Centre, SATMCranfield UniversityBedfordUK

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