This paper explores optimizing Integral-Retarded (IR) controller strategies for first-order linear time-delayed processes. By employing a model for DC motor dynamics, we incorporate a design approach that considers an unintentional delay within the control loop. The IR controller is optimized using meta-heuristic algorithms, specifically genetic algorithms. The optimization framework integrates multi-objective cost functions, balancing system response speed and control efforts. Experimental verification is carried out on a physical test setup, where the controller’s efficacy is validated against a square wave reference signal. The outcomes demonstrate that the IR controller, optimized for maximum exponential decay and control efficiency, significantly enhances the motor’s velocity tracking and response smoothness.

This note introduces a geometric approach to devising a modified variant of the conventional Proportional Integral (PI) controller, termed "Proportional Delayed Integral" (PδI). By including an artificial delay in the integral term, we demonstrate that the proposed scheme improves the decay rate attained by the classical PI controller. The analysis involves evaluating the spectral abscissa and employing a geometrical method in both (kp, ki)-plane and (h, ki)-plane. Several numerical examples illustrate the effectiveness of our proposal.

This paper presents a geometric approach to designing a modified version of the classical PI control called Proportional Delayed Integral (PδI) to obtain the fastest regulation in a type of second-order linear system. Specifically, we first show that by adding an appropriate time delay in the integral component of the PI control, the system achieves a faster response to what can be obtained by using a classical PI control. Then, we outline the conditions under which our delay-based control stabilizes a specific class of second-order systems through an analysis of the spectral abscissa and a graphical approach called D-decomposition. Furthermore, we apply our results to determine the parameters of the fastest regulator.

In this paper we present a simple procedure to design fractional-PDμcontrollers for Single-Input-Single-Output-Linear Time Invariant (SISO-LTI) systems with constant time-delay. More precisely, based on a geometric approach, we present a methodology not only to design a stabilizing controller, but also to provide practical guidelines to design non-fragile PDμcontrollers. Finally, in order to illustrate the simplicity of the proposed approach as well as the efficiency of the PDμcontroller in a realistic scenario, we consider an experimental setup consisting of controlling a teleoperated system using two Phantom Omni haptic devices.

This paper presents an interaction control strategy for industrial robot manipulators which consists of the combination of a calibration-free, vision-based control method with an impedance-control approach. The vision-based, robot control method known as camera-space manipulation is used to generate a given, previously defined trajectory over an arbitrary surface. Then, a kinematic impedance controller is implemented in order to regulate the interaction forces generated by the contact between the robot end-effector and the work surface where the trajectory is traced. The paper presents experimental evidence on how the vision-force sensory fusion is applied to a path-tracking task, using a Fanuc M16-iB industrial robot equipped with a force/torque sensor at the wrist. In this task, several levels of interaction force between the robot end-effector and the surface were defined. As discussed in the paper, such a synergy between the control schemes is seen as a viable alternative for performing industrial maneuvers that require force modulation between the tool held by the robot and the working surface.

This paper presents a methodology for precise robot positioning and path tracking, performed by industrial robots over large surfaces of arbitrary size, shape and orientation. The methodology is based on a vision-based, calibration-free robot control method known as camera-space manipulation. The path, defined and stored in a CAD file, is later adapted to the curved, work-surface by using a mapping procedure. When applied to large surfaces, the precision of the positioning and path-tracking maneuvers depends on several factors like the resolution of the cameras per unit physical space and the mapping procedure, which may introduce distortion specially in the case of non-developable surfaces. In order to reduce the influence of camera-resolution, this paper presents two alternatives: the use of multiple cameras and the application of cameras mounted over non-expensive, sensorless pan/tilt units. In the case of the distortion produced by the mapping procedure, the paper discusses several options like a modified geodesic mapping and virtual projection. The proposed techniques were tested multiple times over flat and deformed surfaces, by using a large work-envelope, industrial robot.

This paper presents a new version of the camera-space-manipulation method (CSM). The set of nonlinear view parameters of the classic CSM is replaced with a linear model. Simulations and experiments show a similar precision error for the two methods. However, the new approach is simpler to implement and is faster.

The paper presents an alternative to CNC machining, based on a proposed method for creating very large and precise replicas of prototype shapes using material-removal and/or material-adding mechanisms that need not be calibrated. The method is based upon the creation of a ldquovirtual moldrdquo, which is created in the two-dimensional image planes of two or more stationary, uncalibrated cameras. The cameras are placed so as to view portions of the prototype surface and remain stationary while multiple-beam laser pointers cast their light toward the prototype shape and the resulting laser-spot reflections are registered and matched among the cameras. Large numbers of images can be acquired with slightly offset pan and tilt angles of laser-pointer-bearing units, resulting in collected laser-spot-centroid indications that may number in the thousands. The spot-centroid coordinates in camera space are matched in such a way that individual, physical spot-centroid indications are registered in memory in accordance with correspondence among those cameras able to view any one particular spot. This forms the basis of the ldquovirtual moldrdquo. Subsequent reproduction of the shape, as with a CNC machine, relies upon action of a robot to remove material from a blank. This blank is placed so as to occupy the region where the prototype had been during laser spot casting. Camera-space manipulation is used to guide the robot in consecutive passes of material removal, with laser spots cast upon each newly revealed intermediate surface and reflected up into the original cameras. The paper presents the use of a FANUC M16-iB industrial robot, in order to obtain experimental evidence on how the original surface regions can be replicated with extremely high precision despite no need for calibration either of the cameras or the manipulator.

Current industrial robot-programming methods require, depending on the task to be developed, an elevated degree of technical ability and time from a human operator, in order to obtain a precise, nonoptimal result. This correspondence paper presents a methodology used to generate an optimal sequence of robot configurations that enable a precise point-allocating task applicable, for instance, to spot-welding, drilling, or electronic component placement maneuvers. The optimization process starts from a nonoptimal, initial sequence designated intuitively by a human operator using an easy-to-use interface. In this correspondence paper, intuitive programming is considered as the process of defining, in a computer graphics environment and with a limited user knowledge of robotics or the industrial task, the sequence of motions that enable the execution of a complex industrial robotic maneuver. Such an initial sequence is later followed by a robot, very precisely, using a vision-based, calibration-free, robot control method. Further robot path optimization is performed with a genetic algorithm approach. An industrial robot, which is part of the experimental setup, was used in order to validate the proposed procedure.

This paper presents aspects related to the generation and tracking of closed trajectories over an arbitrary surface of unknown geometry. Such a capacity is required in some of the most important industrial robotic tasks, like the cutting or welding of commercial plates. Previous work has shown how a calibration-free, vision-based method can be combined with an optimal geodesic-mapping approach, in order to generate an optimal trajectory that traces a previously defined path, stored as a CAD model, over an arbitrary, curved surface. The application of this technique in the case of non-developable surfaces did not achieve closure when a closed-trajectory was attempted. This paper presents a methodology for successfully achieving closure of a given closed-path, when this is traced over a non-developable surface. The proposed technique was tested using an industrial robot and a vision-based system that included structured lighting for image-analysis simplification. The results of these experiments are reported herein.

This paper presents aspects related to the development of a technique for three-dimensional path tracking over unstructured surfaces. Path tracking is performed by an industrial robot, using a vision-based technique known as camera-space manipulation. In this work a previously-defined, three-dimensional trajectory is placed, in an optimal fashion, over a curved, unstructured surface. The method was tested with an industrial Fanuc ArcMate 100i robot, together with structured lighting in the form of a matrix array of laser beams. Such source of light provides a way to facilitate the image-analysis process required to characterize the surface where the task is going to be performed. A demanding industrial task such as welding was performed with the methodology presented herein. Experimental results show a complex path welded over a surface of unknown geometry.

The paper introduces a new estimation approach to the method of camera-space manipulation-a robust and precise means of controlling 3-dimensional robot maneuvers using vision. This approach reduces the computational and memory burden required by the formerly used "batch" estimation approach while retaining identical results. The discussion includes actual experimental results wherein reliable, millimeter positioning precision with a 3-dimensional, rigid-body task is achieved using a very large GMF S400 robot.