Danil Kulminskiy

This paper presents a practical approach to fully automated kinematic calibration of an industrial manipulator. The approach is based on the principle of plane constraint. The electrical signal is used to fix the moment of contact between the conductive tool and the flat surface. The measurement data are manipulator configurations (joint angles) at the moment of contact. A modification of the algorithm to deal with the scaling problem is also proposed. This approach provides both high calibration accuracy and lower cost of the experimental setup compared to coordinate measuring machines (CMMs), laser trackers, and vision systems. The article examines the impact of various methods of kinematic parameterization of manipulators: the Denavit – Hartenberg agreement (DH), product of exponentials (POE), as well as the complete and parametrically continuous model (CPC) on the calibration accuracy. A comparison is made of the open-loop and the proposed closed-loop calibration methods on the Puma 560 model known in the literature. POE parameters were converted to DH and CPC to compare accuracy after calibration based on these parameterizations. The method of computing POE-CPC transformation as a solution to a certain optimization problem is proposed. The problem of identifying geometric parameters in the presence of restrictions is solved by gradient optimization methods. Experiments have been carried out on an ABB IRB 1600 industrial manipulator with an installed conductive probe and an ABB IRBP A-500 robotic positioner with a conductive metal flat surface. A technique for indirectly checking the accuracy of calibration of kinematic parameters is proposed based on a study of the accuracy of manipulation when using these parameters. A comparison is made of the manipulation accuracy when using four sets of parameters: nominal parameters obtained during factory calibration with the Leica AT901B laser tracker and two sets of parameters obtained by applying the proposed calibration method. The kinematic parameters obtained from the experiment determine more accurately the position of the manipulator TCP for part of the configuration working space, even for areas that were not used for calibration.

The paper experimentally investigates the problem of the influence of periodic vibrations of the pivot point of a physical pendulum on its nonlinear oscillations in the vicinity of a stable equilibrium position on the vertical. The vibrations are assumed to be periodic and occur in the plane of the pendulum’s motion along an elliptical trajectory. In the experimental plane of parameters: the amplitude of pendulum oscillations and the parameter characterizing the difference in the vibration intensity of the pivot point in the horizontal and vertical directions, the values at which the pendulum clock gains and delays are selected. The experiment showed that with a vibration of $7.0$ Hz, which is more intense in the horizontal direction, the oscillation period of the pendulum angle increases by $0.017$ seconds compared to the pendulum’s natural period. In contrast, with vibration more intense in the vertical direction, the period decreases by $0.0164$ seconds. The experiments were carried out on an ABB IRB $1600$ industrial robot manipulator with a developed pendulum and a reflector with a lens system for a laser tracker installed at the end effector of the robot. Tracking of the trajectory of the pendulum pivot point was carried out using an API Radian Pro laser tracker, the amplitude and frequency of pendulum oscillations were recorded using a machine vision camera and image processing methods.

This article presents the results of a study exploring sensorimotor integration in upperlimb prostheses through the development of a prototype noninvasive adaptive control system for a bionic hand prosthesis. The study focuses on creating sensory feedback that replicates the properties of biofeedback with a focus on signals from the fingertips, unlike most studies that focus on recognizing patterns in electromyogramm (EMG) signals. The prototype integrates a twocomponent sensor system into a bionic hand prosthesis model with five independent servomotors. This system consists of a surface EMG sensor, which detects muscle activation intent, and thinfilm resistive pressure sensors embedded in the fingertips. The algorithm processes normalized EMG and pressure data in real time using a programmable microcontroller, implementing closedloop grip force adjustment. Key developments include dynamic calibration using the RMS signal envelope, multi-input PID controllers (tuned using the Ziegler – Nichols method) to minimize overshoot, and low-latency force adaptation for objects with variable compliance. The study also included numerical simulations using the Kelvin – Voigt contact model to simulate fingertip contact with soft and rigid materials. A series of experiments using the proposed prototype were conducted for comparison with the numerical simulations. The experimental results are consistent with the numerical simulations, with a smoother increase in force observed when interacting with the soft material. However, the experimental data differ from the model data for a given force setpoint and also have a dead zone associated with the characteristics of the force sensors used in the prototype. This research lays the foundation for accessible adaptive prosthetics and has direct applications in robotic systems.

This study introduces an approach for open-loop geometric calibration of industrial manipulators that integrates three widely used kinematic formulations: Denavit – Hartenberg (DH), Product of Exponentials (POE), and Complete Parametric Continuous (CPC) models. The proposed method focuses on identifying optimal measurement configurations within a local, spatially narrow workspace, which is a common operational scenario in industrial robotic applications. To achieve high calibration efficiency, a linear approximation model was employed, and the measurement configurations were selected using the D-optimality criterion to maximize parameter identifiability. Experimental validation was performed on an ABB IRB 1600 (10/1.45) manipulator equipped with an API Radian Laser Tracker EMSD3 measurement system, providing a linear accuracy of 0.7 $\mu$m per meter. The system was equipped with a Smart Track Sensor offering an orientation accuracy of 0.005 degrees. Independent measurement sets were used for experiments for each model in several variations to identify the best parameter estimates that can be used in the future for this robot. The results demonstrate a substantial enhancement in calibration accuracy. Specifically, applying the POE-based identification procedure within the narrow workspace region reduced the average error in the Tool Center Point (TCP) position by a factor of 22 when compared to the uncalibrated nominal parameters, with the mean error decreasing from 2.852 mm to 0.13 mm. Additionally, the repeatability analysis showed that the standard deviation of TCP position errors across repeated measurements did not exceed 0.007 mm. These results confirm that the proposed approach ensures high calibration precision and robustness suitable for high-accuracy industrial robotic tasks.