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Several real-world applications introduce derivativefree optimization problems, called variable dimension problems, where the problem's dimension is not known in advance. Despite their importance, no unified framework for developing, comparing, and benchmarking variable dimension problems exists. The robot arm controlling problem is a variable dimension problem where the number of joints to optimize defines the problem's dimension. For a holistic study of global optimization methods, we studied 14 representative methods from 4 different categories, i.e., (i) local search optimization techniques with random restarts, (ii) state-of-the-art DIRECT-type methods, (iii) established Evolutionary Computation approaches, and (iv) state-of-the-art Evolutionary Computation approaches. To investigate the effect of the problem's dimensionality on the solution we generated 20 instances of various combinations among the number of predefined and open decision variables, and we performed experiments for various computational budgets. The results attest that the robot arm controlling problem provides a proper benchmark for variable dimensions. Furthermore, methods in-corporating local search techniques have dominant performance for higher dimensionalities of the problem, while state-of-the-art EC methods dominate in the lower dimensionalities.

Dual-arm robots can overcome grasping force and payload limitations of a single arm by jointly grasping an object. However, if the distribution of mass of the grasped object is not even, each arm will experience different wrenches that can exceed its payload limits. In this work, we consider the problem of balancing the wrenches experienced by a dual-arm robot grasping a rigid tray. The distribution of wrenches among the robot arms changes due to objects being placed on the tray. We present an approach to reduce the wrench imbalance among arms through discrete bimanual manipulation. Our approach is based on sequential sliding motions of the grasp points on the surface of the object, to attain a more balanced configuration. We validate our modeling approach and system design through a set of robot experiments., QC 20210315Part of proceeding: ISBN 978-172817395-5

In this work, we address the problem of executing in-hand manipulation based on visual input. Given an initial grasp, the robot has to change its grasp configuration without releasing the object. We propose a method for in-hand manipulation planning and execution based on information on the object's shape using a dual-Arm robot. From the available information on the object, which can be a complete point cloud but also partial data, our method plans a sequence of rotations and translations to reconfigure the object's pose. This sequence is executed using non-prehensile pushes defined as relative motions between the two robot arms., QC 20211221

[ES] El impacto es la parte más peligrosa de una tarea con contacto. Su duración es muy breve por lo que es necesario un control extremadamente rápido. Durante el impacto, le energía cinética del robot adquirida en movimiento libre se transforma en potencial elástica y viceversa. Este artículo propone la conmutación de los parámetros de la impedancia mecánica de forma a aumentar la disipación de la energía del sistema y, de esta forma, suavizar el impacto., [EN] The impact is the most dangerous part of a contact task. Its duration is very brief; hence an extremely fast control is necessary. During the impact, the kinetic energy of the robot acquired during free motion is transformed into elastic potential energy and vice versa. This article proposes the commutation of the parameters of the mechanical impedance in order to increase the dissipation of the energy of the system, and thus to smooth the impact.

[ES] El impacto es la parte más peligrosa de una tarea con contacto. Su duración es muy breve por lo que es necesario un control extremadamente rápido. Durante el impacto, le energía cinética del robot adquirida en movimiento libre se transforma en potencial elástica y viceversa. Este artículo propone la conmutación de los parámetros de la impedancia mecánica de forma a aumentar la disipación de la energía del sistema y, de esta forma, suavizar el impacto., [EN] The impact is the most dangerous part of a contact task. Its duration is very brief; hence an extremely fast control is necessary. During the impact, the kinetic energy of the robot acquired during free motion is transformed into elastic potential energy and vice versa. This article proposes the commutation of the parameters of the mechanical impedance in order to increase the dissipation of the energy of the system, and thus to smooth the impact.

[ES] El impacto es la parte más peligrosa de una tarea con contacto. Su duración es muy breve por lo que es necesario un control extremadamente rápido. Durante el impacto, le energía cinética del robot adquirida en movimiento libre se transforma en potencial elástica y viceversa. Este artículo propone la conmutación de los parámetros de la impedancia mecánica de forma a aumentar la disipación de la energía del sistema y, de esta forma, suavizar el impacto., [EN] The impact is the most dangerous part of a contact task. Its duration is very brief; hence an extremely fast control is necessary. During the impact, the kinetic energy of the robot acquired during free motion is transformed into elastic potential energy and vice versa. This article proposes the commutation of the parameters of the mechanical impedance in order to increase the dissipation of the energy of the system, and thus to smooth the impact.

[ES] El impacto es la parte más peligrosa de una tarea con contacto. Su duración es muy breve por lo que es necesario un control extremadamente rápido. Durante el impacto, le energía cinética del robot adquirida en movimiento libre se transforma en potencial elástica y viceversa. Este artículo propone la conmutación de los parámetros de la impedancia mecánica de forma a aumentar la disipación de la energía del sistema y, de esta forma, suavizar el impacto., [EN] The impact is the most dangerous part of a contact task. Its duration is very brief; hence an extremely fast control is necessary. During the impact, the kinetic energy of the robot acquired during free motion is transformed into elastic potential energy and vice versa. This article proposes the commutation of the parameters of the mechanical impedance in order to increase the dissipation of the energy of the system, and thus to smooth the impact.

[ES] El impacto es la parte más peligrosa de una tarea con contacto. Su duración es muy breve por lo que es necesario un control extremadamente rápido. Durante el impacto, le energía cinética del robot adquirida en movimiento libre se transforma en potencial elástica y viceversa. Este artículo propone la conmutación de los parámetros de la impedancia mecánica de forma a aumentar la disipación de la energía del sistema y, de esta forma, suavizar el impacto., [EN] The impact is the most dangerous part of a contact task. Its duration is very brief; hence an extremely fast control is necessary. During the impact, the kinetic energy of the robot acquired during free motion is transformed into elastic potential energy and vice versa. This article proposes the commutation of the parameters of the mechanical impedance in order to increase the dissipation of the energy of the system, and thus to smooth the impact.

[ES] El impacto es la parte más peligrosa de una tarea con contacto. Su duración es muy breve por lo que es necesario un control extremadamente rápido. Durante el impacto, le energía cinética del robot adquirida en movimiento libre se transforma en potencial elástica y viceversa. Este artículo propone la conmutación de los parámetros de la impedancia mecánica de forma a aumentar la disipación de la energía del sistema y, de esta forma, suavizar el impacto., [EN] The impact is the most dangerous part of a contact task. Its duration is very brief; hence an extremely fast control is necessary. During the impact, the kinetic energy of the robot acquired during free motion is transformed into elastic potential energy and vice versa. This article proposes the commutation of the parameters of the mechanical impedance in order to increase the dissipation of the energy of the system, and thus to smooth the impact.

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.

There are several common approaches used to obtain the kinematic and dynamic equations which describe the motion of robot manipulators. However, a problem arises when these conventional body oriented robot arm kinematic equations are used to simulate the manipulator motion. In this case, the Jacobian matrix which relates the end effector motion to joint angle variations becomes singular when two successive arm links align. When the robot arm passes through these singular points, the jacobian matrix is not invertible, and as a result of this, the motion cannot be simulated. This thesis investigates how this situation can be avoided by using a Newton Euler approach to variable definition, and using the equations interpreted in a fixed references frame.

The classical mover's problem is the following: can a rigid object in 3-dimensional space be moved from one given position to another while avoiding obstacles? It is known that a more general version of this problem involving objects with movable joints is PSPACE complete, even for a simple tree-like structure moving in a 3-dimensional region. In this paper, we investigate a 2-dimensional mover's problem in which the object is a robot arm with an arbitrary number of joints. In particular, we give a polynomial time algorithm for moving an arm confined within a circle from one given configuration to another. We also give a polynomial time algorithm for moving the arm from its initial position to a position in which the end of the arm reaches a given point within the circle. (Author)