Global Path Planning Method for Parks based on Complete Coverage Cleaning Task

Xiaoke Ming; Shaodong Jiang; Yue Duan

doi:10.54097/fcis.v4i1.9421

Authors

Xiaoke Ming
Shaodong Jiang
Yue Duan

DOI:

https://doi.org/10.54097/fcis.v4i1.9421

Keywords:

Low Speed Driverless Technology, Complete Coverage Path Planning, Park Sanitation

Abstract

In this paper, based on a small driving sanitation platform of an enterprise, the global path planning method in the unmanned decision system is studied and designed for the characteristics of the park environment and the task requirements. The operation space of the sanitation platform is divided into rectangular square cleaning area and lane cleaning area based on the task demand of full coverage of the park. For the sweeping task of the lane area, multiple parallel sweeping reference paths are generated by raster erosion of the lane map; for the sweeping task of the rectangular square, this paper proposes an improved bow-shaped full coverage algorithm combining forward and reverse based on the steering capacity constraint of the sanitation vehicle. Finally, the path articulation algorithm is used to connect the sweeping paths of suboperating areas to form a global reference path for the sweeping operation of the park.

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References

Choset H. Coverage for robotics–a survey of recent results[J]. Annals of mathematics and artificial intelligence, 2001, 31: 113-126.

Choset H, Pignon P. Coverage path planning: The boustrophedon cellular decomposition[C]//Field and service robotics. Springer London, 1998: 203-209.

Choset H. Coverage of known spaces: The boustrophedon cellular decomposition[J]. Autonomous Robots, 2000, 9: 247-253.

Kyaw P T, Paing A, Thu T T, et al. Coverage path planning for decomposition reconfigurable grid-maps using deep reinforcement learning based travelling salesman problem[J]. IEEE Access, 2020, 8: 225945-225956.

Boschian V, Pruski A. Grid modeling of robot cells: A memory-efficient approach[J]. Journal of Intelligent and robotic Systems, 1993, 8: 201-223.

Han L, Yashiro H, Nejad H T N, et al. Bezier curve based path planning for autonomous vehicle in urban environment [C]// 2010 IEEE intelligent vehicles symposium. IEEE, 2010: 1036-1042.

Zhang S, Wu Y, Ogai H. Spatial attention for autonomous decision-making in highway scene[C]//2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). IEEE, 2020: 1435-1440.

Shkel A M, Lumelsky V. Classification of the Dubins set[J]. Robotics and Autonomous Systems, 2001, 34(4): 179-202.