Topics in Modelling, Motion Planning and Control for Underactuated Mechanical Systems
dynamic constraints, mechanical systems with one or several passive degrees of freedom, trajectory planning based on nested representation of a forced motion, moving Poincare sections, transverse coordinates, transverse linearization, Lyapunov, Poincare and Zhukovski stability, walking robots, hybrid transverse linearization, sensitivity analysis, non-prehensile manipulation, AI-tools for robotics
Recorded Introductory Lecture
Short Course SummaryThe course helps students systematically explore topics of modern robotics and nonlinear control theory focused on developing scalable methods for performing and analyzing agile movements of dynamically constrained robotic systems. Modeling, motion planning and control algorithms for such systems become important and unavoidable, for instance, in describing problem settings for automating various labor-intensive tasks such as grasping, manipulating or handling of external objects performed nowadays in industry and service applications primarily by humans. Most of dynamic constraints in applications are case specific or linked to scenarios of work of mechanisms. Meanwhile, some constraints are generic and can be simultaneously present in describing behaviors of quite distant nonlinear systems. Constraints due to under-actuation provide examples of such generic structural features of nonlinear mechanical systems.
The main part of lectures emphasize challenges of model based and first principles approaches to handle and overcome such and similar constraints. The other part of the course includes lectures devoted to illustrating theoretical arguments, and to practicing on available software and hardware realization of the methods developed for solving trajectory planning and control assignments for performing non-prehensile manipulation of a passive disc on a hand of a Butterfly robot. The idea of the robot and the problem to be solved can be devised from the movies:
Organization of the courseThe course is developed for graduate students interested in modelling, motion planning and control for under-actuated mechanical systems. The material is organized around four complimentary themes that help gradually enter and explore the subject:
- Introduction to Underactuated Systems: Examples, concepts, math and models for planning, control and analysis
- Motion and Trajectory Planning for Underactuated Systems: Nested representation and motion generator of a robot behavior; analytic and computational steps in parametrizing agile behaviors; AI-tools in searching feasible behaviors; examples
- Motion Control for Underactuated Systems: Transverse dynamics; Andronov-Vitt theorem; (hybrid) transverse linearization for a motion of a controlled mechanical system; numerical methods, challenges and examples
- Case study: Planning and performing non-prehensile manipulation of a passive disc on a hand of the "Butterfly robot"
The syllabus of the lectures can be found here.
The literature, the lectures are based on, can be found here.
Scheduled Activities and Past RecordsIn 2022 the course will be run at
- 2022, August-November: Department of Engineering Cybernetics, Norwegian University of Science and Technology, Norway. Contact person: Dr. Anton Shiriaev.
The graduate course was previously read at
- Department of Automatic Control, Lund University, Sweden. Contact persons: Dr. Anders Robertsson, Dr. Rolf Johansson.
- Institute of Robotics, Innopolis University, Russia. Contact person: Dr. Aleksandr Klimchik.
- Departamento de Ingenieria, de Control y Robotica, Division de Ingenieria Electrica, Facultad de Ingenieria, UNAM, Mexico. Contact person: Dr. Leonid Fridman.
- Dutch Institute of Systems and Control (DISC), Utrecht, The Netherlands. Contact person: Dr. Henk Nijmeijer.
- School of Electrical Engineering, Royal Institute of Technology (KTH), Sweden. Contact person: Dr. Karl Henrik Johansson.
- Doctoral school in Information Technology and Electrical Engineering, Universita degli Studi di Napoli Federico II, Italy. Contact persons: Dr. Fabio Ruggiero, Dr. Bruno Siciliano.
- I2S doctoral school, Laboratoire dInformatique, de Robotique et de Microelectronique de Montpellier (LIRMM), Montpellier University and the French National Center for Scientific Research (CNRS), France. Contact person: Dr. Ahmed Chemori.