By Alla G. Kravets
Contents
Object Recognition of the Robotic System with Using a Parallel
Convolutional Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Shuai Yin and A. S. Yuschenko
Mathematical Model of a Swarm Robotic System with Wireless
Bi-directional Energy Transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Konstantin Krestovnikov, Ekaterina Cherskikh and Andrey Ronzhin
Pareto Optimal Solutions and Their Application in Designing
Robots and Robotic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Irina Romanova
Collaborative Robotics
Control and Ergonomic Problems of Collaborative Robotics . . . . . . . . . 43
Arkady S. Yuschenko
Human-Robot Interaction Efficiency and Human-Robot
Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Rinat R. Galin and Roman V. Meshcheryakov
Human-Robot Cooperation in Technological Wall Climbing
Robot System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
V. Gradetsky, M. Knyazkov, E. Semenov and A. Sukhanov
Features of Human-Exoskeleton Interaction . . . . . . . . . . . . . . . . . . . . . . 77
V. Gradetsky, I. Ermolov, M. Knyazkov, E. Semenov and A. Sukhanov
Analysis of Dynamics in Human—Exoskeleton Collaborative
System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Anna Matokhina, Alla G. Kravets, Daria Volodina, Stanislav Dragunov
and Vladislav Shashkov
Multi-agent Robotic Systems
Formation Control of Ground Multi-agent System Using Quadcopter
with Camera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Stanislav L. Zenkevich, Anaid V. Nazarova and Jianwen Huo
Dependence of Dynamics of Multi-robot System
on Control Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Vladimir Serebrenny and Madin Shereuzhev
The Application of Multi-agent Robotic Systems
for Earthquake Rescue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Anaid V. Nazarova and Meixin Zhai
About Controlling the Shape of the Sprinkler . . . . . . . . . . . . . . . . . . . . 147
Eugene Briskin, Yaroslav Kalinin, Konstantin Lepetukhin
and Alexander Maloletov
Space Robotics
Modern Space Robotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Pavel P. Belonozhko
Moving-Base Space Robots—Applying Eigen-Dynamics
of a Reduced System to Synthesize Controls . . . . . . . . . . . . . . . . . . . . . 171
Pavel P. Belonozhko
The Concept of Failure- and Fault-Tolerance on Base of the Dynamic
Redundancy for Distributed Control Systems of Spacecraft
Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Irina V. Asharina
Industrial Robotics
Industrial Robotics Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Ivan Ermolov
Development of an Information Control System for a Remotely
Operated Vehicle with Hybrid Propulsion System . . . . . . . . . . . . . . . . . 205
Olga I. Gladkova, Vadim V. Veltishev and Sergey A. Egorov
Control System of a Starting-Landing Platform with Parallel
Kinematics for Pilotless Flying Machines in the Conditions
of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
I. N. Egorov
Intuitive Industrial Robot Programming Interface with Augmented
Reality Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
Alexander Schwandt and Arkady Yuschenko
Preface
This monograph devoted to the analysis of the accumulated experience of modeling and design of robotic systems solutions in Russian and international practice. The authors perform integration of deep learning methods and mathematical modeling in the successful experience of the establishment of robotic systems in the different countries and analyze causal connections of the robotic modeling and design from the positions of new industrial challenges.
The book also describes intelligent control methods for robotic groups on the base of multi-agent theory and describes their control architecture. The authors study the multi-agent control methods’ implementation in conditions of uncertainty and dynamically changing environment.
The book is devoted to studying robotics through the prism of human–robot collaboration. The authors determine the methodological foundations of the collaborative robotic concept as a breakthrough in modern industrial technologies. The book also analyzes the performance and ergonomic problems of the collaborative robotic systems.
The authors substantiate the scientific and methodological approaches to study the modern mechanisms of space robotic development and control. Breakthrough achievements of the last decade defined novel design imperative for space robotics. The authors determine the main features of space robotic design and the key control technologies.
Finally, this book dwells with theoretical foundations of industrial robotics control, formulates its concept within the frameworks of intelligent control methods and theories, and views the peculiarities of control technologies as a specific sphere of modern industrial technologies, which distinguished in the Industry 4.0. The authors study the genesis of mathematical and control methods transformation from directly human-controlled machines to knowledge-based complex robotic systems in the tewenty-first century.
Edition of the book is dedicated to the 105th anniversary of the founder of the Scientific and Educational Center of Bauman Moscow State Technical University Academician E. P. Popov and technically supported by the Engineering Center “Automation and Robotics” of Bauman Moscow State Technical University and the Project Laboratory of Cyber-Physical Systems of Volgograd State Technical University.