Laboratory of Intelligent Robotics Systems
Igor Gaponov
Faculty of Computer Science and Engineering

Lab of Intelligent Robotics Systems

The laboratory carries out research in the fields of design and development of intelligent mechatronic modules, actuators and sensors, wearable robotic systems and exoskeletons, cable- and tendon-driven robots, teleoperation and human-machine interaction. In addition, the laboratory is involved into development and evaluation of energy-efficient control systems for anthropomorphic robotic systems based on static and dynamic equilibrium. 

The research of the laboratory also covers the areas of nonlinear control systems of actuators, mechanisms and robotic systems, identification of static and dynamic parameters of mechatronic systems, as well as the use of machine learning methods for system identification and robot locomotion.

Head of laboratory – Igor Gaponov

activity of laboratory

Research areas:


Robot control systems 

— Anthropomorphic robots and robot locomotion 

— Mechanism and actuator design 

— Design and modeling of complex robotic systems 

— Manipulation and teleoperation 

— Mechatronics, sensorics and perception 

— Additive manufacturing and robot prototyping

Команда

Igor Gaponov 

Head of laboratory 

Kirill Poletkin

Assistant professor 

Oleg Bulichev

PhD student

Mikhail Ivanou

PhD student

Mikhail Ostanin

PhD student

Dmitry Popov,

PhD student

Geesara Prathap

PhD student

Ramil Dautov

PhD student

Dmitry Devitt

PhD student

Simeon Nedelchev

PhD student

Anton Egorov

PhD student

Sami Sellami

PhD student

Valeria Skvortsova

PhD student

PROJECTS

Do you want a joint project?
Contact us

01

Modeling of under/overactuated robotic systems with mechanical compliance

Development of mathematical apparatus to model and control mechanical systems with mechanical flexibility. The resulting mathematical models and control architectures will allow to expand the application range of flexible, under/overacuated robotic systems and will help achieve higher positioning accuracy, energy efficiency, and better static and dynamic performance of the system

02

Design and investigation of dynamic cable-driven systems

This project aims at increasing the payload and control performance of various robotic systems with serial, parallel and hybrid structure using a novel type of actuator (twisted string actuators). Another important research direction here is optimal mechanism design and development of control algorithms that would enable us to fully take advantage of the benefits of this actuator type

03

Development of active wearable robotic systems for efficient and safe human assistance

The main objectives of the project are the synthesis and experimental evaluation of robotic systems that provide physical assistance to humans, as well as modeling and experimental study on the processes of human-machine interaction in application to assistive and rehabilitation robotics. Another important objective of the project is the study of the neuromuscular activity of humans during interaction with active assistive devices incorporating different types of actuators, as well as design optimization of these devices

04

Development of models, methods and algorithms for the calibration of parallel robots with flexible constraints

The project is focused on mathematical modeling of kinematics, statics, and dynamical motion of parallel robots with flexible constraints, as well as on the development of calibration methods and algorithms for this robot type. The developed mathematical apparatus will serve as the basis for modeling and control of cable- and tendon-driven robotic systems for various industrial applications, including additive manufacturing, mechanical processing of large surfaces, mining equipment maintenance, and others

05

Novel variable stiffness actuators and their control algorithms

This project’s main goals are design and evaluation of various actuators with variable and controllable stiffness, which include flexible cable-driven systems and mechanisms with controlled compliance. Variable stiffness actuators can be used in different applications of wearable robotics, collaborative manipulators and anthropomorphic robotic systems to ensure safe contact with the surface during locomotion

06

Cable-driven robots for building construction based on additive manufacturing technology

The project investigates the problems of modeling and control of large-span, cable-driven parallel robots. The main milestones of the project will include software development for modelling and control of such systems, design and evaluation of various methods to construct different shapes, objects and buildings via 3D-printing with concrete, as well as experimental evaluation of various prototypes of concrete-printing robots and their parts

07

Modeling, design and control of tensegrity robotic systems

The project is concerned with finding effective methods to design, control and process sensoric data coming from tensegrity structures that are used in various robotic applications. We develop algorithms based on numerical optimization, classical control theory approaches and machine learning, and develop novel robotic devices based on tensegrity structures

08

Anthropomorphic robots and robot locomotion

The project studies important questions pertinent to the walking robot control, including trajectory planning, preservation of vertical stability during locomotion on rugged terrain, control system stability (including formal methods of the stability analysis of dynamic systems of this kind), design of control laws that take into account the underactuated nature of the system, and robot robustness preservation

09

Machine learning in application to robot control

We are working on the application of machine learning methods to the practical problems of robot control and develop controllers with nontrivial algorithms and heuristics based on automatically generated blocks and collected data. We also study the processes of dataset gathering and preparation and try to solve the problem of transferring modeling results onto real robotic systems