Information-integration-based optimal coverage path planning of agricultural unmanned systems formations: From theory to practice

Industrial information integration engineering (IIIE) is an innovative research subject for analyzing complicated and large-scale systems. Autonomous and efficient path coverage of unmanned systems formations is an important subject of intelligent industrial agriculture. As one typical kind of complicated systems, agricultural unmanned systems formations are urgently required to optimize their operating trajectories. In this paper, an IIIE design for coverage path planning of the agricultural unmanned systems formations is presented as an IIIE application to verify the entire performances with considering the couplings between the formations and the working environment. In this design, one key concept of field-state iteration for information coupling integration is inherited and introduced in detail. Furthermore, its simulation models were developed based on structure (unmanned system agent structure and formation structure), geometry (map model and graph theory), dynamics (unmanned system agent model and formation model), and control (formation coverage path planning, formation control and trajectory recurrence) in the practice environments. The practice results were analyzed to validate the effectiveness of the proposed information integration design. Further, this paper puts forward a coverage path planning scheme for unmanned systems formations based on the rotating beam and improved probability roadmap algorithms, which can maintain 99.8% coverage rate, 0.08% repetition rate, and 0.007% redundant coverage rate while ensuring the optimal time. Then, two types of three-dimensional practice platform software including CarSim and Gazebo, are selected to graft the proposed algorithm into agricultural tractors formation and plant protection UAVs formation respectively, and the feasibility of the algorithm is verified under the condition closest to the real environment. Multiple experimentalresults demonstrate that the algorithm proposed in this paper has superior feasibility for engineering practice.