• Journal of Biosystems Engineering
• /
• v.43 no.4
• /
• pp.273-284
• /
• 2018

Purpose: Conventional headland turning typically requires repeated forward and backward movements to move the farming equipment to the next row. This research focuses on developing an upland agricultural robot with an optimized headland turning mechanism that enables a $180^{\circ}$ turning positioning to the next row in one steering motion designed for a two-wheel steering, four-wheel drive agricultural robot named the HADA-bot. The proposed steering mechanism allows for faster turnings at each headland compared to those of the conventional steering system. Methods: The HADA-bot was designed with 1.7-m wide wheel tracks to travel along the furrows of a garlic bed, and a look-ahead path following algorithm was applied using a real-time kinematic global positioning system signal. Pivot turning tests focused primarily on accuracy regarding the turning radius for the next path matching, saving headland turning time, area, and effort. Results: Several test cases were performed by evaluating right and left turns on two different surfaces: concrete and soil, at three speeds: 1, 2, and 3 km/h. From the left and right side pivot turning results, the percentage of lateral deviation is within the acceptable range of 10% even on the soil surface. This U-turn scheme reduces 67% and 54% of the headland turning time, and 36% and 32% of the required headland area compared to a 50 hp tractor (ISEKI, TA5240, Ehime, Japan) and a riding-type cultivator (CFM-1200, Asia Technology, Deagu, Rep. Korea), respectively. Conclusion: The pivot turning trajectory on both soil and concrete surfaces achieved similar results within the typical operating speed range. Overall, these results prove that the pivot turning mechanism is suitable for improving conventional headland turning by reducing both turning radius and turning time.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.4
• /
• pp.1786-1795
• /
• 2011

The trajectory control for omni-directional mobile robot is not easy. Especially, the tracking control which system uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy multi-layered algorithm. The fuzzy control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. It explains the architecture of a fuzzy adaptive controller using the robust property of a fuzzy controller. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system; related mathematical theorems and their proofs are also given. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.9
• /
• pp.104-114
• /
• 1995

Mathematical models of industrial robots or manipulators are composed of highly nonlinear equations with nonlinear couplings between the variables of motions. These nonlin- earities were not considered important in the first stage that the working speed of the manipulator was not so fast, but the effect of nonlinear forces has become serious, as the working speed has been increased. So more improvement of performance cannot be expected by the control of manipulator using approximate linearization. As an approach for solving these problems, there is a method that eliminates nonlinear theory, which makes possible cecoupling of coupling terms and arbitrary arranging of poles is briefly introduced in this study. When the theory is applied to design the control law, its feasibility is examined whether the reasonable control results are obtained by simulating position, velocity, torque and tracing trajectory. The relations between the coefficients of the linearized differential equations and the maximum error and torque for the prescribed trajectory are also examined. Finally, the method for selecting the values for getting the most rapid and precise response within maximum torque of each drive is suggested in the choice of coefficients of characteristic equations which are obtained as a result of the control.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.743-746
• /
• 1996

A hybrid control scheme to regulate the force and position by dual arms is proposed, where two arms are treated as one arm in a kinematic viewpoint. Our approach is different from other hybrid control approaches which consider robot dynamics, in the sense that we employ a purely kinematic based approach for hybrid control, with regard to the nature of position-controlled industrial robots. The proposed scheme is applied to sawing task. In the sawing task, the trajectory of the saw grasped by dual arms is planned in an offline fashion. When the trajectory of the saw is planned to follow a line in a horizontal plane, 3 position parameters are to be controlled(i.e, two translational positions and one rotational position). And a certain level of contact force has to be controlled along the vertical direction(i.e., minus z-direction) not to loose the contact with the object to be sawn. Typical feature of sawing task is that the contact position where the force control is to be performed is continuously changing. Therefore, the kinematic mapping between the force controlled position and the joint actuators has to be updated continuously. The effectiveness of the proposed control scheme is experimentally demonstrated. The proposed hybrid control scheme can be applied to arbitrary dual arm systems, regardless of their kinematic structure and the number of actuated joints.

• Journal of information and communication convergence engineering
• /
• v.7 no.2
• /
• pp.119-124
• /
• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.4
• /
• pp.474-483
• /
• 2003

Belt drives provide freedom to position the motor relative to the load and this phenomenon enables reduction of the robot arm inertia. It also facilitates quick response when employed in robotics. Unfortunately, the flexible dynamics deteriorates the positioning accuracy. Therefore, there exists a trade-off between the simplicity of the control strategy to reject time varying disturbance caused by flexibility of the belt and precision in performance. Resonance of the system further leads to vibrations and poor accuracy in positioning. In this paper, accurate positioning of a belt driven mechanism using a feed-forward compensator under maximum acceleration and velocity constraints is proposed. The proposed method plans the desired trajectory and modifies it to compensate delay dynamics and vibration. Being an offline method, the proposed method could be easily and effectively adopted to the existing systems without any modification of the hardware setup. The effectiveness of the proposed method was proven by experiments carried out with an actual belt driven system. The accuracy of the simulation study based on numerical methods was also verified with the analytical solutions derived.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.2
• /
• pp.101-106
• /
• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.12
• /
• pp.1021-1026
• /
• 2016

The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.40 no.2
• /
• pp.19-25
• /
• 2003

For a class of multi-input multi-output nonlinear systems which perform a given task repetitively, an extended type of a direct leaning control (DLC) is proposed using the information on the (vector) relative degree of a multi-input multi-output system. Existing DLC methods are observed to be applied to a limited class of systems with the relative degree one and a new DLC law is suggested which can be applied to systems having higher relative degree. Using the proposed control law, the control input corresponding to the new desired output trajectory is synthesized directly based on the control inputs obtained from the learning process for other output trajectories. To show the validity and the performance of the proposed DLC, simulations are performed for trajectory tracking control of a two-axis SCARA robot.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.11
• /
• pp.898-906
• /
• 2014

This paper presents a reduction method for a straight-line path error of a flexible beam deploying from a rotating rigid hub. Previous studies discussed about only vibration phenomena of flexible beams deploying from rotating hubs; however, this study investigates a vibration reduction of a rotating beam with variable length. The equation of motion and associated boundary conditions are derived for a flexible beam deploying from a rotating rigid hub, and then they are transformed to a variational equation. By applying the Galerkin method, the discretized equations are obtained from the variational equation. Based on the discretized equations, the dynamic responses of a rotating/deploying beam are analyzed when the beam end has a straight line motion. A reduction method for the trajectory error is proposed, using the average length of a rotating/deploying beam. It is shown that the proposed method is able to reduce the residual vibration of a rotating/deploying beam.