This year we celebrate the 70-th year of the chair founded in BMSTU in 1951 which name today is "Robotic Systems and Mechatronics". Evolution of the chair during the last 70 years is completely reflected the technical progress in the field of automation. From automatic drives to autonomous robots. Again with the improvement of the educational programs in accordance with the vital demands the chair managed to keep the basic traditions of the Russian engineering school based on the combination of the fundamental scientific background with the practical competence in the new technical systems design. The prominent scientists and engineers made a major contribution to the content and methods of training of future specialists in robotics and mechatronics which are acknowledged both in Russia and abroad. Nowadays robotics is transforming from perspective direction to urgent needs. The chair "Robotic Systems and Mechatronics" is completely ready to reply the new challenge of time.

Collaborative robotics progress is based on the possibility to apply robots to the wide range activity of peoples. Now the user can control the robot without any special knowledge in robotics and safe. The price of such possibilities is complication of control system of robot which now has to aquire an opportunity of autonomous behavior under human’s control, using the necessary sensors and elements of artificial intelligence. In our research we suppose the collaborative robot as mobile robotic device possible to fulfil some work under the human’s speech demands not only in the same space with the human. We also suppose the necessity of bilateral dialogue human-robot to make it clear the task, the current situation, the state as robot as human. The complex task of control, or may be the collaboration of human with his artificial partner need new means of control, situation recognition, speech dialogue management. As a mean to solve the whole complex of problems we propose the combination of different artificial neural networks. Such as convolution networks for image recognition, deep networks for speech recognition, LSTM networks for autonomous movement of robot control in current situation. Investigations in the field of mobile and manipulation robots including the human-robot control have been proceeded for some years in the department "Robotic systems and mechatronics" BMSTU celebrating now it 70th years Jubilee. The reader may find some of the works in the bibliography. In result of all these investigations we obtain the service robot model which may find a wide application.

In order to search and rescue injured during earthquake, we proposed a method for multi-robots motion planning and distributed control in this paper. At first, we have created two probabilistic search models to considering the search area and the characteristics of sensors, which we used to search the injured targets. And after finding the targets, they are assigned to the mobile robots on the land to afford emergency rescue. In order to reach to the targets, a path planning method based on map matching is proposed. There are three parts here. Firstly, to obtain the global and local map: continuous ground images are first collected using the UAV’s vision system, and subsequently, a global map of the ground environment is created by processing the collected images. The local map of the ground environment is obtained using the 2D laser radar sensor of the leader (UGA). Established the coordinate conversion relationship between UAV and UGV, unknown values during map matching are determined via the least square method. Secondly, our robots moved by group (leader-follower). The leader’s path was planned globally and locally. The other multi-robots moved along the path planned by the leader. Thirdly, in order to plan and coordinate the robots in the group, the finite state machine is used to describe the logical level of control system for each robot in the group. After that, at the tactical level of the control system, the movement control law of formation maintaining mode and formation switching mode is designed.

The article deals with the design of a walking robot with gripping devices that allow the robot to move on arbitrarily oriented surfaces in space. Such robots are relevant primarily for the inspection of various industrial structures. A model of a two-support robot with gripping devices that allow it to be attached to support surfaces with a small curvature, but arbitrarily oriented in space, is proposed. To ensure attachment to the support surfaces, the robot is designed with five degrees of freedom. An important criterion is the possibility of dexterous movement on surfaces. One of the degrees of freedom of the robot was made linear, which makes it easier to step over obstacles and allows you to implement simpler walking algorithms. When the robot is attached to the supporting surfaces by two gripping devices at once, the kinematic chain is closed. This can lead to an increase in forces and moments in the robot’s links. In this paper, it is applied to use two methods of controlling the drives of the links together – the implementation of impedance control by introducing feedback on the evaluation of the moment based on the motor currents and ensuring the pliability of the gripping devices due to its own elasticity. A mathematical simulation of the robot was carried out, which showed the possibility of reducing the forces in the robot links when attaching the robot to two support surfaces at the same time. The best results were achieved when controlling the current vector of a synchronous motor and using current signals to implement impedance control.

The actual problem of determining all six coordinates of the current position of a mobile robot (unmanned aerial vehicle) from 3D-range-finding images (point clouds) generated by an onboard 3D laser sensor when moving (flying) in an unknown environment is considered. An extreme navigation algorithm based on using multidimensional optimization methods is proposed. The rules for calculating the difference between 3D images of the external environment used for optimization of the functional are described. The form of the functional of the difference of 3D images for different environments (premises, industrial-urban environment, rugged and wooded areas) has been investigated. Requirements for the characteristics of the sensor and the geometry of the external environment are formulated, the fulfillment of which ensures the correct formulation and solution of the problem of extreme navigation. The optimal methods of scanning the surrounding space are described and the conditions are substantiated, the fulfillment of which ensures the solution of the navigation problem by the proposed algorithm in real time (at the rate of movement) when processing 3D images formed by modern 3D laser sensors. In particular, the dependence between the frequency of formation of 3D images and the angular and linear velocities of motion is described, which ensures that the functional of the difference of 3D images falls into the multidimensional interval of unimodality, which guarantees a direct search of global minimum in real time. Various methods of direct search for the global minimum of the functional are tested and the  fastest for the case under consideration are selected. The accuracy of solving the navigation problem is estimated and a method is proposed to reduce the accumulated error, based on using an older 3D image for correcting the calculated value of the current coordinates, which has an intersection of the view area with the current view area. The proposed method, which is a modification of the reference image method, allows reduce the total error, which grows in proportion to the number of cycles of solving the extreme navigation problem, to values that ensure the autonomous functioning of transport robots and UAVs in previously unprepared and unknown environments. The effectiveness of the proposed algorithmic and developed software and hardware for extreme navigation is confirmed by field experiments carried out in real conditions of various environments.

The walking mobile robots (WMR) have recently become widely popular in robotics. They are especially useful in the extreme cases: search and rescue operations; cargo delivery over highly rough terrain; building a map. These robots also serve to explore and describe a partially or completely non-deterministic workspace, as well as to explore areas that are dangerous to human life. One of the main requirements for these WMR is the robustness of its control system. It allows WMR to maintain the operability when the characteristics of the support surface change as well as under more severe conditions, in particular, loss of controllability or damage of the supporting limb (SL). We propose to use the principles of genetic programming to create a WMR control system that allows a robot to adapt to possible changes in its kinematics, as well as to the characteristics of the support surface on which it moves. This approach does not require strong computational power or a strict formal classification of possible damage to the WMR. This article discusses two main WMR control modes: standard, which accord to a serviceable kinematics, and emergency, in which one or more SL drives are damaged or lost controllability. As an example, the structure of the control system of the WMP is proposed, the kinematics of which is partially destroyed in the process of movement. We developed a method for controlling such robot, which is based on the use of a genetic algorithm in conjunction with the Mealy machine. Modeling of modes of movement of WMR with six SL was carried out in the V-REP program for two cases of injury: absent and not functioning limb. We present the results of simulation of emergency gaits for these configurations of WMP and the effectiveness of the proposed method in the case of damage to the kinematic scheme. We also compared the performance of the genetic algorithm for the damaged WMR with the standard control algorithm.

The article is devoted to the application of a group of robotic complexes for military purposes. The current state of control systems of single robotic complexes does not allow solving all the tasks assigned to the robot. The analysis of methods of controlling a group of robots in combat conditions is carried out. The necessity of using a multi-level control system for an intelligent combat robot is justified. A multi-level control system for an intelligent robot is proposed. Such a system assumes the possibility of controlling the robot in one of four modes: remote, supervisory, autonomous and group. Moreover, each robot, depending on the external conditions and its condition, can be in any control mode. The application of the technique is shown by the example of the movement of a group of robots with an interval along the front. The problem of the movement of slave robots behind the leader is considered. When forming the robot control algorithm, the method of finite automata was used. The algorithm controls the movement of the RTK in various operating modes: group control mode and autonomous movement mode. In the group control mode, the task is implemented: movement for the leader. For the state of "Movement in formation", an algorithm for forming the trajectory of the movement of guided robots was implemented. An algorithm for approximating the Bezier curve was used. It allows you to build a trajectory for the slave robot. On the basis of the obtained trajectory, the angular and linear velocity were calculated. In the autonomous control mode, two tasks are solved: moving to a given point and avoiding obstacles. Vector Field Histogram was used as an algorithm for detouring an obstacle, which determines the direction of movement without obstacles. The state of "Movement to a given point" is based on Pure Pursuit as a simple and reliable algorithm for solving such problems. A computer model of the movement of a group of robots was developed. The model is implemented in the MATLAB program using the Simulink and Mobile Robotics Simulation Toolbox libraries. Several different variants of the movement of the RTK group are modeled, which differ from each other in the initial location of the robots and the position of obstacles. The conducted computer simulation showed the efficiency and effectiveness of the proposed method of RTC control.