Complete coverage path planning algorithm based on energy compensation and obstacle vectorization

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 real-time 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.