LIRMM UMR CNRS 5506
Université de Montpellier
24 Mai 2018, 14.00
salle des commissions, bât Polytech
Campus de St. Jérôme
Control of Complex Robotic Systems:
Challenges, Design and Experiments
Robotics was initially and for a long time guided by needs in industry. Indeed, the early years of robotics was largely focused on robot manipulators, used mainly for simple and repetitive automation tasks. The first industrial robot manipulator appeared in 1961 in the assembly lines of General Motors. The early control systems for robot manipulators were designed to control independently each axis of the robot as a Single-Input-Single-Output (SISO) linear system. Linear automatic control theory was then extensively used in this basic solution, where the coupling dynamics between the different axes of the robot were often neglected and the robot model significantly simplified. Beyond these issues, the main barriers to progress were the high cost of computation, the lack of good sensors, and the lack of fundamental understanding of robot dynamics. However, the progress of robotics and automation as well as their associated innovative applications has required the consideration of more and more complex tasks needing high performances. These challenging tasks required a deeply understanding of complex nonlinear dynamics of robots. Besides, it has also motivated the development of new theoretical advances in different control fields (robust, adaptive, etc.), which has consequently enabled more sophisticated applications. Nowadays, robotic control systems are highly advanced, including manipulation robotics, underwater robotics, aerial robotics, mobile robotics, medical robotics, parallel robotics, wearable robotics, humanoid robotics and more others. In this lecture the main challenges related to control of robotic systems will be emphasized, and illustrated through different applications in robotics. For each of these fields, the motivations and the need of developing advanced control schemes will be first highlighted. Then some proposed advanced control solutions will be introduced and illustrated through real-time experiments.