Dynamic function allocation of agricultural robot vehicle controlled by man-machine cooperation Dynamic function allocation of agricultural robot vehicle controlled by man-machine cooperation*

doi:10.12398/j.issn.2096-7217.2020.01.004

Abstract

Abstract: It is necessary to distribute functions reasonably between a human operator and an automation system in a teleoperated agricultural robotic tractor to accomplish a task cooperatively. This paper proposes a strategy of dynamic function allocation on the basis of a BP neural network, genetic algorithm and adaptive genetic algorithm. Here, the operator's state, workload, and task demand are chosen as trigger mechanism of dynamic function allocation. Then, a traditional BP neural network, genetic algorithm based BP neural network, and adaptive genetic algorithm based BP neural network are established by taking the operator's state, workload, and task demand as inputs of the network and automation level as output. The three network are compared to obtain more effective dynamic function allocation. Simulation tests show that the adaptive genetic algorithm based BP neural network has minimum training time and has highest prediction accuracy.

Key words: teleoperation, agricultural robot, function allocation, man-machine cooperation, genetic algorithm, adaptive genetic algorithm, BP neural network

Tingting Mao, Shuxian Dong, Jinlin Xue. Dynamic function allocation of agricultural robot vehicle controlled by man-machine cooperation Dynamic function allocation of agricultural robot vehicle controlled by man-machine cooperation^*[J]. Journal of Intelligent Agricultural Mechanization (in Chinese and English), 2020, 1(1): 24-31.

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Dynamic function allocation of agricultural robot vehicle controlled by man-machine cooperation Dynamic function allocation of agricultural robot vehicle controlled by man-machine cooperation^*

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