Autonomous Travel of Lettuce Harvester using Model Predictive Control. Issue 30 (2019)

• Record Type: Journal Article
• Authors: Mitsuhashi, T.; Chida, Y.; Tanemura, M.
• Is Part Of: IFAC-PapersOnLine. Volume 52:Issue 30(2019)
• Page Start: 155
• Page End: 160
• Publication Date: 2019
• Subjects: Autonomous vehicles -- Harvester -- Tracked vehicle -- On-off actuators -- Model predictive control -- Nonlinear models -- Time-state Control Form; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2019.12.514
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 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.