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37 results on '"Satici, Aykut C."'

1. Robustness of Control Design via Bayesian Learning

Author

Ashenafi, Nardos Ayele, Sirichotiyakul, Wankun, and Satici, Aykut C.

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

In the realm of supervised learning, Bayesian learning has shown robust predictive capabilities under input and parameter perturbations. Inspired by these findings, we demonstrate the robustness properties of Bayesian learning in the control search task. We seek to find a linear controller that stabilizes a one-dimensional open-loop unstable stochastic system. We compare two methods to deduce the controller: the first (deterministic) one assumes perfect knowledge of system parameter and state, the second takes into account uncertainties in both and employs Bayesian learning to compute a posterior distribution for the controller.

Published
2022

2. Nonholonomic Rolling Nonprehensile Manipulation Primitive

Author

Gutierrez-Giles, Alejandro, Satici, Aykut C., Donaire, Alejandro, Ruggiero, Fabio, Lippiello, Vincenzo, Siciliano, Bruno, Siciliano, Bruno, Series Editor, Khatib, Oussama, Series Editor, Amato, Nancy, Advisory Editor, Brock, Oliver, Advisory Editor, Bruyninckx, Herman, Advisory Editor, Burgard, Wolfram, Advisory Editor, Chatila, Raja, Advisory Editor, Chaumette, Francois, Advisory Editor, Chung, Wan Kyun, Advisory Editor, Corke, Peter, Advisory Editor, Dario, Paolo, Advisory Editor, De Luca, Alessandro, Advisory Editor, Dillmann, Rüdiger, Advisory Editor, Goldberg, Ken, Advisory Editor, Hollerbach, John, Advisory Editor, Kavraki, Lydia E., Advisory Editor, Kumar, Vijay, Advisory Editor, Nelson, Bradley J., Advisory Editor, Park, Frank Chongwoo, Advisory Editor, Salcudean, S. E., Advisory Editor, Siegwart, Roland, Advisory Editor, Sukhatme, Gaurav S., Advisory Editor, and Ruggiero, Fabio, editor

Published
2022
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3. A Coordinate-Free Framework for Robotic Pizza Tossing and Catching

Author

Satici, Aykut C., Ruggiero, Fabio, Lippiello, Vincenzo, Siciliano, Bruno, Siciliano, Bruno, Series Editor, Khatib, Oussama, Series Editor, Amato, Nancy, Advisory Editor, Brock, Oliver, Advisory Editor, Bruyninckx, Herman, Advisory Editor, Burgard, Wolfram, Advisory Editor, Chatila, Raja, Advisory Editor, Chaumette, Francois, Advisory Editor, Chung, Wan Kyun, Advisory Editor, Corke, Peter, Advisory Editor, Dario, Paolo, Advisory Editor, De Luca, Alessandro, Advisory Editor, Dillmann, Rüdiger, Advisory Editor, Goldberg, Ken, Advisory Editor, Hollerbach, John, Advisory Editor, Kavraki, Lydia E., Advisory Editor, Kumar, Vijay, Advisory Editor, Nelson, Bradley J., Advisory Editor, Park, Frank Chongwoo, Advisory Editor, Salcudean, S. E., Advisory Editor, Siegwart, Roland, Advisory Editor, Sukhatme, Gaurav S., Advisory Editor, and Ruggiero, Fabio, editor

Published
2022
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4. Data-Driven Design of Energy-Shaping Controllers for Swing-Up Control of Underactuated Robots

Author

Sirichotiyakul, Wankun, Satici, Aykut C., Siciliano, Bruno, Series Editor, Khatib, Oussama, Series Editor, Antonelli, Gianluca, Advisory Editor, Fox, Dieter, Advisory Editor, Harada, Kensuke, Advisory Editor, Hsieh, M. Ani, Advisory Editor, Kröger, Torsten, Advisory Editor, Kulic, Dana, Advisory Editor, Park, Jaeheung, Advisory Editor, and Laschi, Cecilia, editor

Published
2021
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5. Nonprehensile Manipulation Control and Task Planning for Deformable Object Manipulation: Results from the RoDyMan Project

Author

Ruggiero, Fabio, Kim, Jung-Tae, Gutierrez-Giles, Alejandro, Satici, Aykut C., Donaire, Alejandro, Cacace, Jonathan, Buonocore, Luca Rosario, Fontanelli, Giuseppe Andrea, Lippiello, Vincenzo, Siciliano, Bruno, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Gusikhin, Oleg, editor, and Madani, Kurosh, editor

Published
2020
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8. Nonprehensile Manipulation Control and Task Planning for Deformable Object Manipulation: Results from the RoDyMan Project

Author

Ruggiero, Fabio, primary, Kim, Jung-Tae, additional, Gutierrez-Giles, Alejandro, additional, Satici, Aykut C., additional, Donaire, Alejandro, additional, Cacace, Jonathan, additional, Buonocore, Luca Rosario, additional, Fontanelli, Giuseppe Andrea, additional, Lippiello, Vincenzo, additional, and Siciliano, Bruno, additional

Published
2019
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12. Data-driven passivity-based control of underactuated mechanical systems via interconnection and damping assignment.

Author

Sirichotiyakul, Wankun and Satici, Aykut C.

Subjects
*PASSIVITY-based control, *NONLINEAR differential equations, *PARTIAL differential equations, *BENCHMARK problems (Computer science), *INVERTED pendulum (Control theory), *STABILITY theory
Abstract

Since its introduction in the late 1980s, passivity-based control (PBC) has proven to be successful in controlling many robotic systems. The connection between stability and passivity theory is the most attractive feature of controllers designed using this methodology. However, the need to solve nonlinear partial differential equations (PDE) in closed-form has been a major challenge in applying PBC to general robotic systems. Here, we introduce a systematic approach to design controllers for a class of underactuated mechanical systems based on interconnection and damping assignment. Exploiting the universal approximation capability of neural networks, we formulate a data-driven optimisation problem that discovers solutions to the required PDEs automatically. Our approach does not destroy the passivity structure, preserving the inherent stability properties. We demonstrate the efficacy of our framework on two benchmark problems: the inertia wheel pendulum and the ball and beam system. [ABSTRACT FROM AUTHOR]

Published
2023
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22. Nonprehensile Manipulation of Deformable Objects: Achievements and Perspectives from the Robotic Dynamic Manipulation Project

Author

Ruggiero, Fabio, primary, Petit, Antoine, additional, Serra, Diana, additional, Satici, Aykut C., additional, Cacace, Jonathan, additional, Donaire, Alejandro, additional, Ficuciello, Fanny, additional, Buonocore, Luca R., additional, Fontanelli, Giuseppe Andrea, additional, Lippiello, Vincenzo, additional, Villani, Luigi, additional, and Siciliano, Bruno, additional

Published
2018
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33. Formation control of wheeled robots with vision-based position measurement.

Author

Poonawala, Hasan, Satici, Aykut C, Gans, Nicholas, and Spong, Mark W

Abstract

Many applications require multiple mobile robots to move with a common velocity and at fixed relative distances. We present a time-invariant, state-feedback control law and a novel vision-based pose reconstruction system that allows one differential drive robot to follow another at a constant relative distance. The control law does not require measurement or estimation of the leader robot velocity and has tunable parameters that allows one to prioritize the error bounds of the desired states. The proposed pose reconstruction algorithm is computationally inexpensive and reliable. We present experimental results on two iRobot Create robots showing the performance of the controller and vision algorithm. [ABSTRACT FROM PUBLISHER]

Published
2012
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35. Time-Optimal Paths for a Robotic Batting Task

Author

Fabio Ruggiero, Aykut C. Satici, Vincenzo Lippiello, Diana Serra, Bruno Siciliano, Kurosh MadaniDimitri PeaucelleOleg Gusikhin, Serra, Diana, Ruggiero, Fabio, Satici, Aykut C., Lippiello, Vincenzo, and Siciliano, Bruno

Subjects
Constant linear velocity, Kinematic inversion, Control theory, Computer science, Ball (bearing), Paddle, Robot, Free flight, Minification, Time optimal
Abstract

This paper presents a novel method to optimize the motion of a paddle within a nonprehensile batting task. The proposed approach shows that it is possible to online predict the impact time and the configuration of the paddle, in terms of its linear velocity and orientation, to re-direct a ball towards a desired location, imposing also a desired spin during the free flight. While exploiting the hybrid dynamics of the task during the minimization process, the obtained position and orientation paths are planned by minimizing the acceleration function of the paddle in SE(3). The batting paths are then tracked by a semi-humanoid robot through a closed-loop kinematic inversion. Numerical tests are implemented to compare different metrics to define the optimal impact time.

Published
2017

36. Intrinsic Euler-Lagrange dynamics and control analysis of the ballbot

Author

Bruno Siciliano, Vincenzo Lippiello, Fabio Ruggiero, Aykut C. Satici, Satici, Aykut C, Ruggiero, Fabio, Lippiello, Vincenzo, and Siciliano, Bruno

Subjects
Equilibrium point, 0209 industrial biotechnology, Underactuation, Ballbot, Linear system, Equations of motion, Mobile robot, 02 engineering and technology, Computer Science::Robotics, Controllability, Nonlinear system, 020901 industrial engineering & automation, Control theory, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Electrical and Electronic Engineering, Mathematics
Abstract

Research on bipedal locomotion has shown that a dynamic walking gait is energetically more efficient than a statically stable one. Analogously, even though statically stable multi-wheeled robots are easier to control, they are energetically less efficient and have low accelerations to avoid tipping over. In contrast, the ballbot is an underactuated, nonholonomically constrained mobile robot, upward equilibrium point of whose body has to stabilized by active controls. In this work, we derive coordinate-invariant equations of motion for the ballbot. We present the linearized equations of motion followed by its controllability analysis. Excluding the rotary degree of freedom of the ball in the inertial vertical direction, the linear system turns out to be controllable. It follows that the nonlinear system is locally controllable and we provide a proportional-derivative type controller that locally exponentially stabilizes the upward equilibrium point as well as the translation of the ball. The basin of attraction turns out to be large in the simulation studies.

Published
2016

37. A coordinate-free framework for robotic pizza tossing and catching

Author

Fabio Ruggiero, Vincenzo Lippiello, Bruno Siciliano, Aykut C. Satici, Satici, Aykut C., Ruggiero, Fabio, Lippiello, Vincenzo, and Siciliano, Bruno

Subjects
0209 industrial biotechnology, Mathematical model, media_common.quotation_subject, Work (physics), GRASP, 02 engineering and technology, Inertia, 01 natural sciences, Motion (physics), Computer Science::Robotics, Coordinate-free, 020901 industrial engineering & automation, Control theory, Artificial Intelligence, Control and Systems Engineering, 0103 physical sciences, Optimal trajectory, Electrical and Electronic Engineering, 010306 general physics, Software, Mathematics, media_common
Abstract

This chapter presents a solution to the problem of autonomous pizza tossing and catching. Under the assumption that robotic fingers grasp the pizza dough with soft contact, the grasp constraints are formulated and used to derive the individual and combined Euler-Lagrange dynamic equations of motion of the robotic manipulator and the dough. In particular, the dynamics of the dough is a modified version of the rigid-body dynamics, taking into account the change of inertia due to its deformation. Through these mathematical models, the two control problems of tossing and catching are formulated. For the tossing phase, an exponentially convergent controller that stabilizes a desired velocity of the dough as it leaves the fingers, is derived. On the other hand, to catch the dough, an optimal trajectory for the end-effector of the robotic manipulator is generated. Finally, the control laws to make the optimal trajectory exponentially attractive are derived. The developed theory is demonstrated with an elaborate simulation of the tossing and catching phases. This chapter is based on the work presented in [1].

Published
2016

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