Abstract
To address the poor performance of the existing sweet potato transplanting robots, in this paper, a two-degree-of-freedom sweet potato transplanting robot arm is proposed to improve the transplanting success rate and production yield. Different transplanting strategies, including vertical transplanting, boat-shaped transplanting, and inclined planting, can be achieved for different terrain types. The designed transplanting mechanical arm can achieve both vertical and rotational movement of the seedling claw through the vertical sliding motor and the rotating motor respectively. With the two degrees of freedom, the designed transplanting robot arm can complete various transplanting trajectories on the transplanting plane. Moreover, a transplanting trajectory controller is then designed for the proposed transplanting robot based on a linear model prediction algorithm. To improve the control performance, two control system optimization schemes are proposed: the influence of prediction time length on the accuracy of transplanting trajectory is discussed and the optimal prediction time length value is obtained, and a reference trajectory segmenting control was proposed to improve the real time of sweet potato transplanting. The proposed sweet potato transplanting robot is validated experimentally through field testing. The minimum qualified rate of potato seedling erection angle was 94.7%, and the minimum qualified rate of planting depth was 94.8%. The test proved that the proposed transplanting scheme can realize various transplanting methods of sweet potato with better performance, which satisfies the practical production requirements for mechanical planting of sweet potatoes.
Highlights
Sweet potato is an important raw material for food and starch industries and new energy raw materials in the world [1-5].Transplanting and harvesting of sweet potato production is involved with the largest labor and operating costs, and there is an urgent need to achieve mechanization and intelligence[6-10].The United States, Italy and other countries mostly use efficient chain clamp transplanters that can perform multi-row transplanting at the same time, but only in direct planting mode [11-13].Japan has developed a sweet potato transplanter that uses a four-bar linkage to achieve oblique seedling planting, which has received widespread appreciation [14]
Multifunctional vegetable transplanters are still used as sweet potato transplanting machines in most parts of China, primarily for direct transplanting [15].There are two major issues with current sweet potato transplanting: 1.Mechanized sweet potato transplanters are in short supply
This paper designs a two-degree-of-freedom sweet potato transplanting robot arm and the sweet potato transplanting trajectory is optimized based on the linear model prediction algorithm
Summary
Sweet potato is an important raw material for food and starch industries and new energy raw materials in the world [1-5].Transplanting and harvesting of sweet potato production is involved with the largest labor and operating costs, and there is an urgent need to achieve mechanization and intelligence[6-10].The United States, Italy and other countries mostly use efficient chain clamp transplanters that can perform multi-row transplanting at the same time, but only in direct planting mode [11-13].Japan has developed a sweet potato transplanter that uses a four-bar linkage to achieve oblique seedling planting, which has received widespread appreciation [14]. The current transplanters can only perform oblique or direct transplanting Other transplanting methods, such as horizontal and boat-shaped transplanting, that have excellent commodity properties and high yields, cannot be mechanized. As a result, employing a robot arm as a sweet potato transplanting mechanism is a viable option for addressing the problems that currently plague seedling transplanting operations. From the perspective of MPC, the linearization prediction model is a common real-time optimization scheme. This paper designs a two-degree-of-freedom sweet potato transplanting robot arm and the sweet potato transplanting trajectory is optimized based on the linear model prediction algorithm. 2.A mathematical model of the transplanting robot arm was created, and a model predictive control algorithm was used to optimize the transplanting trajectory, resulting in sweet potato transplanting that met agronomic requirements. 4.Field tests showed that the proposed transplanting mechanism could achieve a variety of sweet potato transplanting trajectories, confirming the correctness of the transplanting mechanism and trajectory algorithm described in this paper
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