摘要：Autonomous travel of agricultural machines/robots is achieved by movement along a straight line based on a map with the global positioning system (GPS). However, when farm produce such as lettuce is not grown in a straight line, the robots equipped with GPS might damage the lettuce intended for harvesting. With regard to this problem, autonomous travel using local information can improve harvesting accuracy. In this paper, we propose an autonomous travel method for a lettuce harvester with on-off actuators based on the relative positions of the lettuce and the harvest machine obtained via a camera. This study adopts model predictive control (MPC) to ensure that the vehicle follows the positions of some lettuce located ahead in the same line if the vehicle includes the restriction of turning radius. To facilitate the application of an optimal method for determining an optimal input sequence in MPC, we transform a kinematics model of the vehicle into the time-state control form. The effectiveness of the proposed method is shown through numerical examples.
关键词：KeywordsAutonomous vehiclesHarvesterTracked vehicleOn-off actuatorsModel predictive controlNonlinear modelsTime-state Control Form
