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Kinematical Modelling and Its Analytical Inverse Kinematic Solution for the Handling Mechanism of an Agricultural Robot
Title
Kinematical Modelling and Its Analytical Inverse Kinematic Solution for the Handling Mechanism of an Agricultural Robot.
Creator
Defterli, Sinem, Xu, Yunjun, Lin, Kuo-Chi, Zheng, Qipeng, Song, Sang-Eun, University of Central Florida
Abstract / Description
Early detection of the crop diseases helps to prevent failure in the amount and the quality of the production. In agricultural robotics, the idea of a disease detection robot is a fresh and an innovative hot-button topic. The exclusion of the diseased parts from the strawberry plants for further analyses is one of the main tasks of a recently developed strawberry robot. To this purpose, the handling mechanism in the robot needs to achieve an accurate manipulation task to reach the target....
Show moreEarly detection of the crop diseases helps to prevent failure in the amount and the quality of the production. In agricultural robotics, the idea of a disease detection robot is a fresh and an innovative hot-button topic. The exclusion of the diseased parts from the strawberry plants for further analyses is one of the main tasks of a recently developed strawberry robot. To this purpose, the handling mechanism in the robot needs to achieve an accurate manipulation task to reach the target. Reaching, cutting and storing the diseased leaf are challenging and delicate processes during the procedure of the handling mechanism operation in the field.The manipulation task of the mechanism is succeeded when the inverse kinematic relations from workspace to joint space are defined properly. The inverse kinematic analysis is usually subjected to the restrictions due to the limitations in mechanical design of the mechanism, hardware components and operation environment of the robots as well as the morphology of the target. This study proposes a set of analytical algorithms to solve the inverse kinematics problem of the handling mechanism under certain constraints. First, proposed analytical approach is based on the calculation of the joint variables by solving only the 3D position information of the target since the output from image processing algorithms of vision subsystem in the ground robot is only the location of the diseased point. The position of target point is the only output from vision subsystem and this data will be given as an input to the proposed algorithms. Second, the mechanism has certain restrictions on its geometrical construction and the joint actuators' capacity. Hence, these restrictions limit the range of joint variables to be solved. Due to sudden and unpredicted nature of field conditions, the quickness of handling mechanism inverse kinematics solution's execution has a vital effect on the success of the picking task of the robot. Another essential factor is to use the battery life of the robot effectively, by minimizing energy consumption. Therefore, the effectiveness of the proposed algorithm is decided by comparing the developed performance indices of consumed energy and CPU time cost via numerical solution namely, a nonlinear constrained optimization method under same restrictions of inverse kinematics problem. Performance of both algorithms is observed by the simulations in MATLAB(&)#174; and laboratory set-up experiments.
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Date Issued
2016
Identifier
CFE0006291, ucf:51588
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006291
Bio-Inspired Visual Servo Control of a Picking Mechanism in an Agricultural Ground Robot
Title
Bio-Inspired Visual Servo Control of a Picking Mechanism in an Agricultural Ground Robot.
Creator
Defterli, Sinem, Xu, Yunjun, Kauffman, Jeffrey L., Lin, Kuo-Chi, Song, Sang-Eun, Zheng, Qipeng, University of Central Florida
Abstract / Description
For a recently constructed disease detection agricultural ground robot, the segregation of unhealthy leaves fromstrawberry plants is a major task of the robot's manipulation subsystem in field operations. In this dissertation, the motion planning of a custom-designedpicking mechanism in the ground robot's subsystem is studied in two sections. First, a set of analytical, suboptimal semi-analyticaland numerical algorithms are studied to solve the inverse kinematics problem of the handling...
Show moreFor a recently constructed disease detection agricultural ground robot, the segregation of unhealthy leaves fromstrawberry plants is a major task of the robot's manipulation subsystem in field operations. In this dissertation, the motion planning of a custom-designedpicking mechanism in the ground robot's subsystem is studied in two sections. First, a set of analytical, suboptimal semi-analyticaland numerical algorithms are studied to solve the inverse kinematics problem of the handling mechanism in firmcircumstances. These premeditated approaches are built on the computation of the joint variables by an identified 3Dposition data of the target leaf only. The outcomes of the three solution algorithms are evaluated in terms of the performanceindexes of energy change and the CPU time cost. The resultant postures of the mechanism for different target pointlocations are observed both in simulations and the hardware experiments with each IK solution. Secondly, after the manipulation task of the mechanism via the proposed inverse kinematicalgorithms is performed, some compensation may be needed due to the sudden and unpredicted deviation of the targetposition under field conditions.For the purpose of finding optimal joint values under certain constraints, a trajectory optimization problem in image-based visual servoing method via the camera-in-handconfiguration is initiated when the end-effector is in the close proximity of the target leaf. In this part of the study, a bio-inspired trajectory optimization problem in image-basedvisual servoing method is constructed based on the mathematical model derived from the prey-predatorrelationships in nature. In this biological phenomenon, the predator constructs its path in a certain subspace whilecatching the prey. When this motion strategy is applied to trajectory optimization problems, it causes a significantreduce in the computation cost since it finds the optimum solution in a certain manifold. The performance of the introducedbio-inspired trajectory optimization in visual servoing is validated with the hardware experiments both in laboratory settings and in fieldconditions.
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Date Issued
2018
Identifier
CFE0007170, ucf:52247
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007170