Our unique mechatronic laboratory system presents a set of well-documented unique guided challenges within the nonlinear control of mechatronic systems aimed at the creation of stable periodic motions. The task is inspired and directly connected to such topics as humanoid robot locomotion, flexible grasping with non-prehensile manipulation, and other modern cutting edge research topics in robotics.
The Butterfly Robot is a unique laboratory software/hardware bundle that is designed to illustrate state-of-the-art technology and to provide hands-on experience for students to supplement theoretical methods covered within such standard university courses on Bachelor or Master of Science levels as:
- Nonlinear control theory
- Robot Modelling and Control
- Computer vision
- Real-time control or Embedded systems
For each of these courses, a set of experimental tutorials is suggested along with supplementary materials, which will help students to familiarize themselves with basic principles studied within these courses. The Butterfly Robot’s working principle is based on cutting edge developments in the nonlinear control theory. As a result, it will be also of interest for Ph.D. students and researchers in the field. The equipment is supplied with a set of numerical models, which will allow simulation of the dynamical processes in Python or Matlab/Simulink that in turn will simplify development of control algorithms.
One of the key benefits of «Butterfly» Robot is that while being safe to operate it contains simplified versions of major components that are typically present in all industrial robotic systems, such as: an actuator, a mechatronic part, a computer vision system, an embedded real-time rapid control prototyping system. The image analysis for computer vision and the real- time control implementation are performed by separate computing units. This will allow students to get hands-on experience in design and architecture of distributed control systems as well.
Sample experiments for a «Computer vision» course
1. Camera calibration: identification of parameters of the camera and the scene
2. Image recognition and objects classification
3. Estimation of coordinates and of a velocity of an object from a video stream
4. Image processing algorithms, their implementation, and optimization for real-time control systems
Sample experiments for a «Control Systems» course
1. Dynamical systems modeling, parameters identification, filtration algorithms and estimation of state-space variables from external measurements
2. Linearization of a nonlinear dynamical system in a vicinity of an equilibrium point, stabilization of an unstable equilibrium of a nonlinear system
3. Classical and advanced motion tracking algorithms
4. Linear quadratic optimal control problem
Sample experiments for a «Robotics» course
1. Modeling, numerical simulation, identification, and analysis of underactuated systems and systems with nonprehensile constraints
2. Motion planning for underactuated systems taking into account reaction forces imposed by nonprehensile contacts
3. Classical and advanced methods of motion stabilization