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Complete coverage path planning algorithm based on energy compensation and obstacle vectorization
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PRE
AI
DOI：10.1016/j.eswa.2022.117495.png)
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Abstract
En 中文
A complete coverage path planning (CCPP) algorithm based on energy compensation and obstacle vectorization (ECOV) is proposed. The algorithm can be used in demanding fields such as disinfection robots due to its advantages, such as a low path coverage repetition rate and high coverage rate. The algorithm builds an energy map, classifies various obstacles, and proposes separate special area definitions and corresponding energy reconstruction methods for various types of obstacles. Through the energy compensation of the path and the realtime and non-real-time energy reconstruction of special areas of various obstacles, the robot can adapt to more complicated map models and obtain improved results. The proposed algorithm has strong sensitivity to various complex obstacles. Furthermore, the concept of map parity is proposed. Experimental analysis showed that the algorithm is not sensitive to the map parity of the map model, and the parity will not have a large impact on the algorithm due to the minor changes in the actual environment.
Keywords:
Complete coverage path planning
Energy map
Energy compensation
Obstacle vectorization
Map parity
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W
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