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  • 101.
    Yedeg, Esubalewe Lakie
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Wadbro, Eddie
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    State constrained optimal control of a ball pitching robot2013In: Mechanism and machine theory, ISSN 0094-114X, E-ISSN 1873-3999, Vol. 69, p. 337-349Article in journal (Refereed)
    Abstract [en]

    We present a method for offline optimal control of a two-link ball pitching robot with the aim of throwing a ball as far as possible. The pitching robot is connected to a motor via a non-linear torsional spring at the shoulder joint. The elbow joint is passive and loaded with a linear torsional spring. We model the system based on an Euler–Lagrange formulation. Constraints on the motor torque and power as well as the angular velocity of the motor shaft are included in the model. By using an interior point method with gradients supplied by a discrete adjoint method, we numerically solve the resulting constrained control problem of finding the optimal piecewise constant motor torque profile and release position. Numerical experiments illustrate the effectiveness of our strategy as well as the effect of the constraints on the objective. In our experiments, the optimal motor torque gives rise to motions comprising an initial backswing; a transition, where the elbow spring accumulates potential energy; and finally a fast acceleration phase leading up the ball release.

  • 102.
    Yung, I
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Automation of front-end loaders: electronic self leveling and payload estimation2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A growing population is driving automatization in agricultural industry to strive for more productive arable land. Being part of this process, this work is aimed to investigate the possibility to implement sensor-based automation in a particular system called Front End Loader, which is a lifting arms that is commonly mounted on the front of a tractor. Two main tasks are considered here, namely Electronic Self Leveling (ESL) and payload estimation. To propose commercially implementable solutions for these tasks, specific objectives are set, which are: 1) to propose a controller to perform ESL under typical disturbances 2) to propose a methodology for payload estimation considering realistic estimation conditions. Lastly, aligned with these goals, 3) to propose models for the Front End Loader under consideration for derivation of solutions of the specified tasks.

    The self-leveling task assists farmers in maintaining the angular position of the mounted implements, e.g. a bale handler or a bucket, with respect to the ground when the loader is manually lifted or lowered. Experimental results show that different controllers are required in lifting and lowering motions to maintain the implement's angular position with a required accuracy due to principle differences in gravity impact. The gravity helps the necessary correction in lifting motion, but works against the correction in lowering motions. This led us to propose a controller with a proportional term, a discontinuous term and an on-line disturbance estimation and compensation as well as the tuning procedure to achieve a 2 degrees tracking error for lowering motions in steady state. The proposed controller shows less sensitive performance to lowering velocity, as the main disturbance, in comparison to a linear controller.

    The second task, payload estimation, assists farmers to work within safety range as well as to work with a weight measurement tool. A mechanical model derived based on equations of motion is improved by a pressure based friction to sufficiently accurately represent the motion of the front end loader under consideration. The proposed model satisfies the desired estimation accuracy of 2\% full scale error in a certain estimation condition domain in constant velocity regions, with off-line calibration step and off-line payload estimation step. An on-line version of the estimation based on Recursive Least Squares also fulfills the desired accuracy, while keeping the calibration step off-line.

  • 103.
    Yung, I
    et al.
    Umeå University. Ålö AB, Brännland 300 Umeå, Sweden .
    Freidovich, Leonid
    Umeå University.
    Vazquez, Carlos
    Ålö AB.
    Payload Estimation in Front-End Loaders2016Conference paper (Other academic)
    Abstract [en]

    A methodology based on an equation of motion and a two-steps off-line optimization procedure is proposed and investigated to estimate a payload in an industry-standard Front-End Loader. The location of the boom center of gravity is first calibrated via optimization using a known payload to become the base to estimate an unknown payload. This method is compared to an existing method and is verified to be less sensitive to different estimation conditions. Moreover, it also requires less additional operations in the calibration phase.

  • 104.
    Yung, I
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Freidovich, Leonid
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Vázquez, Carlos
    Improvement of Model-Based Payload Estimation for Agricutural Front-End LoadersManuscript (preprint) (Other academic)
    Abstract [en]

    We consider here the development of a better payload estimation system for an agricultural Front-End Loader, equipped with position and pressure sensors, that enable monitoring of various routine operations. We show that an additional pressure-based friction model improves the achievable accuracy of the estimation procedure for payload estimation based on equations of motion. Preceded by estimating the friction parameters in the calibration step, the improvement is verified by employing the updated model in off-line payload estimations for an industry standard Front-End Loader with different estimation conditions under consideration. The overall estimation accuracy is below 2% full scale error. This performance is also maintained in the online implementation of the second step.

  • 105.
    Zhao, Keyi
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Mobile Robot equipped with Laser Pointer for Planning and Intentions2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The demands of mobile robots system are growing rapidly in recent days. Autonomous and semi-autonomous mobile robots for indoor environments have become great helper to human, such as transport robot in warehouse, cleaning robot for apartment and various humanoids for personal assistance, education and space exploration.

    This thesis project work describes how to implement a mobile robot system for unstructured indoor environment. This mobile robot system is able to build a map of the environment, plan path and navigate robot between user-defined locations in the environment autonomously or teleoperated by human through GUI or keyboard on a remote control terminal. Additionally, this mobile robot will be equipped a laser pointer worked as an interaction interface between robot and human by showing robot intensions to operator or surroundings.

    The development of this project work will involve two rapid growing features, one is depth camera and the other is ROS. Use depth camera as the primary sensor has been accepted by more and more mobile robot platform. ROS, as the fast-growing robot software framework, is an inevitable path when developing robot systems.

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