Estimating Natural Frequencies of Cartesian 3D Printer Based on Kinematic Scheme

Nowadays, 3D printers based on Cartesian kinematics are becoming extremely popular due to their reliability and inexpensiveness. In the early stages of the 3D printer design, once it is chosen to use the Cartesian kinematics, it is always necessary to select relative positions of axes and linear drives (prismatic joints), which would be optimal for the particular specification. Within the class of Cartesian mechanics, many designs are possible. Using the Euler–Lagrange formalism, this paper introduces a method for estimating the natural frequencies of Cartesian 3D printers based on the kinematic scheme. Comparison with the finite element method and experimental validation of the proposed method are given. The method can help to develop preliminary designs of Cartesian 3D printers and is especially useful for emerging 3D-printing technologies

Image preprocessing for artistic robotic painting

Artistic robotic painting implies creating a picture on canvas according to a brushstroke map preliminarily computed from a source image. To make the painting look closer to the human artwork, the source image should be preprocessed to render the effects usually created by artists. In this paper, we consider three preprocessing effects: aerial perspective, gamut compression and brushstroke coherence. We propose an algorithm for aerial perspective amplification based on principles of light scattering using a depth map, an algorithm for gamut compression using nonlinear hue transformation and an algorithm for image gradient filtering for obtaining a well-coherent brushstroke map with a reduced number of brushstrokes, required for practical robotic painting. The described algorithms allow interactive image correction and make the final rendering look closer to a manually painted artwork. To illustrate our proposals, we render several test images on a computer and paint a monochromatic image on canvas with a painting robot

Interactive Robot for Playing Russian Checkers

Human\u2013robot interaction in board games is a rapidly developing field of robotics. This paper presents a robot capable of playing Russian checkers designed for entertaining, training, and research purposes. Its control program is based on a novel unsupervised self-learning algorithm inspired by AlphaZero and represents the first successful attempt of using this approach in the checkers game. The main engineering challenge in mechanics is to develop a board state acquisition system non-sensitive to lighting conditions, which is achieved by rejecting computer vision and utilizing magnetic sensors instead. An original robot face is designed to endow the robot an ability to express its attributed emotional state. Testing the robot at open-air multiday exhibitions shows the robustness of the design to difficult exploitation conditions and the high interest of visitors to the robot

Interactive Robot for Playing Russian Checkers

Human–robot interaction in board games is a rapidly developing field of robotics. This paper presents a robot capable of playing Russian checkers designed for entertaining, training, and research purposes. Its control program is based on a novel unsupervised self-learning algorithm inspired by AlphaZero and represents the first successful attempt of using this approach in the checkers game. The main engineering challenge in mechanics is to develop a board state acquisition system non-sensitive to lighting conditions, which is achieved by rejecting computer vision and utilizing magnetic sensors instead. An original robot face is designed to endow the robot an ability to express its attributed emotional state. Testing the robot at open-air multiday exhibitions shows the robustness of the design to difficult exploitation conditions and the high interest of visitors to the robot

A Robot for Artistic Painting in Authentic Colors

Artistic robotic painting automates the process of creating an artwork. This complex and challenging task includes several aspects: creating algorithms for rendering brushstrokes, reproducing the exact shape of a brushstroke, and developing the principles of mixing paints. This work contributes to the previously unsolved problem of accurately reproducing colors of brushstrokes by means of artistic paints. The main contributions of this paper include: the development of a novel 4-component data-driven mathematical model for artistic paint mixing; the design and implementation of a novel robot capable of accurately dosing and mixing acrylic paints thanks to the improved syringe pumps and the innovative paint mixer; the development of a novel pneumatic system for paint release with a build-in clogging detection mechanism. The capabilities of the designed robotic system are demonstrated by painting four artworks: replicas of Claude Monet’s and Arkady Rylov’s landscapes, a synthetic image generated using the StyleGAN2 neural network trained on Vincent van Gogh’s artistic heritage, and a synthetic image generated using the Midjourney neural network. The obtained results can be useful in various applications of computer creativity, as well as in artistic image replication and restoration, and also in colored 3D printing

Comparing the Finite-Difference Schemes in the Simulation of Shunted Josephson Junctions

The paper provides investigation of the numerical effects in finite-difference models of RLC-shunted circuit simulating Josephson junction. We study digital models of the circuit obtained by explicit, implicit and semi-explicit Euler methods. The Dormand-Prince 8 ODE solver is used for verification as a reference method. Two aspects of the RLC- shunted Josephson junction model are considered: the dynamical maps (two-dimensional bifurcation diagrams) and chaotic transients existing in the system within a certain parameter range. We show that both explicit and implicit Euler methods distort the dynamical properties, including stretching or compressing the dynamical maps and changing chaotic transient lifetime decay curve. Experiments demonstrate high reliability of the first-order Euler-Cromer method in simulation of the shunted Josephson junction model which yields data close to the reference data. Obtained results bring new accurate chaotic transient lifetime decay equation for the RLC-shunted Josephson junction model