Research projects
Hamiltonian approach for large-scale multibody systems
The main objective of this project is to develop and investigate highly efficient methods for computer-aided modeling and analysis of complex multibody systems in a unified Hamiltonian approach
Efficient optimal control methods for multibody systems
Current problems require engineers to predict how specific parameters or control inputs will affect the behavior of the complex multibody system. The adjoint method is one of the more interesting methods for systematically calculating the gradient.
Physics-Based and Data-Driven Models For Robot Control
The project aims at pushing an area of expertise to (i) integrate MBS formulations with data–driven techniques, (ii) develop a hybrid modeling approach for optimal trajectory generation based on the adjoint method, (iii) assess possibilities of practical applications of the developed hybrid models.
Optimal trajectory planning for redundant manipulators
The Predictive Quadratic Programming Inverse Kinematics with Scaling (PQPIK-S) designed in this project solves this quandary by combining the inverse kinematics (IK) problem with trajectory scaling and solving them simultaneously.
Efficient Methods for Hybrid Rigid-Flexible Multibody Systems
The main aim of the project is to develop general-purpose hybrid (rigid-flexible) modeling methods that will enable reliable simulation of redundantly constrained systems while maintaining high computing efficiency.
Tools and methods for novel robotics systems
The research concerns the design and implementation of real-time control systems, focusing on humanoids, walking machines and autonomous flying devices. Motion synthesis methods and design solutions for novel robotic systems inspired by biology are also investigated.
Reducing children's injuries in road accidents
Solutions are proposed to reduce the risk of serious injuries is the use of safety belts integrated with the child restraint system with pretensioners, load limiters and the airbag