Alexander Maloletov

This paper presents an approach to terrain shape detection using an array of tactile sensors or motor torque and encoders. A sparse point cloud at points where the surface is touched by the robot’s feet is converted into a polygonal mesh and a dense 3D point cloud using α-shapes derived from a 2D Delaunay triangulation. Cloud-to-Cloud (C2C) and Cloud-to-Mesh (C2M) metrics are used to validate the solution. In the study, a mathematical model of the robot-surface system is developed and numerical experiments are performed on the basis of this model. A modification of Delaunay triangulation is proposed to account for impassable or unexplored areas of the surface. The results of mathematical modeling are confirmed in hardware experiments.

This paper discusses how to develop and implement a bimanual teleoperation system using an exoskeleton suit and two collaborative robots. In the mathematical model, two methods of mapping have been implemented: Joint space mapping via direct control and Cartesian space mapping using Saturation in the Null Space. Both methods are verified in simulation using the developed mathematical model and on hardware using KUKA IIWA robots. A pick-and-place experiment is designed, and the corresponding end-effector positions of the master and the slave devices are obtained. Force feedback is introduced using two methods to improve accuracy and to show the applicability not only for collaborative robots but also on industrial manipulators.

This paper highlights the role of game theory in specific control tasks of cable-driven parallel robots. One of the challenges in the modeling of cable systems is the structural nonlinearity of cables, rather long cables can only be pulled but not pushed. Therefore, the vector of forces in configuration space must consist of only nonnegative components. Technically, the problem of distribution of tension forces can be turned into the problem of nonnegative least squares. Nevertheless, in the current work the game interpretation of the problem of distribution of tension forces is given. According to the proposed approach, the cables become actors and two examples of cooperative games are shown, linear production game and voting game. For the linear production game the resources are the forces in configuration space and the product is the wrench vector in the operational space of a robot. For the voting game the actors can form coalitions to reach the most effective composition of the vector of forces in configuration space. The problem of distribution of forces in the cable system of a robot is divided into two problems: that of preloading and that of counteraction. The problem of preloading is set as a problem of null-space of the Jacobian matrix. The problem of counteraction is set as a problem of cooperative game. Then the sets of optimal solutions obtained are approximated with a fuzzy control surface for the problem of preloading, and game solutions are ready to use as is for the problem of counteraction. The methods have been applied to solve problems of large-sized cable-driven parallel robot, and the results are shown in examples with numerical simulation.

This paper deals with the application of force sensors to estimate position errors of the center of mass of the mobile platform of a cable-driven parallel robot. Conditions of deformations of cables and towers of the robot are included in the numerical model and external disturbance is included too. The method for estimating the error in positioning via force sensors is sensitive to the magnitude of spatial oscillations of the mobile platform. To reduce torsional vibrations of the mobile platform around the vertical axis, a dynamic damper has been included into the system.

Cable-driven parallel robots (CDPR) represent an emerging field of research that has vast applications across different fields of science and engineering, such as medical, aerospace, construction, etc. Dynamic modeling plays an important role in understanding the behavior of these complex systems as well as in enhancing their performances. The state of the art in cable-driven parallel robots (CDPRs) is thoroughly summarized in this review, which covers both basic ideas and cutting-edge advancements in a variety of design modeling control and application domains. The study starts with a thorough examination of the geometric layout and essential elements of CDPR systems describing how the special arrangement of flexible cables allows for better workspace scalability and dynamic performance. It also looks at the complex kinematic and dynamic models that portray the nonlinear behaviors that are essential for attaining accurate motion control like cable sagging elasticity and friction. The optimization of workspace and tension distribution is prioritized in order to preserve system stability and energy efficiency. Furthermore, the review looks at a number of control and planning strategies such as motion planning methods and advanced algorithms like reinforcement learning which guarantee reliable trajectory tracking and operational safety. The wide-ranging effects of CDPR technology are demonstrated through a variety of case studies in the fields of construction entertainment, medical care, agriculture, disaster response, material handling, and space research. Lastly, new developments that promise to improve the capabilities and uptake of CDPRs in next-generation robotic systems are explored, including the incorporation of artificial intelligence machine learning and innovative materials.