Speaker: Salah Bazzi, Postdoctoral Research Associate in the Action Lab at Northeastern University
Title: Soft Nonholonomic Constraints: Theory and Applications to Optimal Control
Efficient motion is an important aspect of robotic locomotion. Even for the simplest wheeled robots, an exact description of the fastest paths that the robot can follow is only known in special cases. Moreover, these known optimal solutions are infeasible in practice since they are derived based on kinematic models of the robots. Attempts to find the optimal trajectories for dynamically-extended models have shown that the optimal control will exhibit chattering, which is also impractical due to the infinite number of control switches required.
In this talk, I will present a new approach for addressing the problem of chattering arising in the time-optimal trajectories of dynamically-extended models of wheeled robots, thereby bringing the theoretical optimal solutions closer to practical feasibility. This approach is based on the relaxation of the nonholonomic constraints in the robot model, such that they incorporate skidding effects. Rather than resorting to existing skidding models, we develop a new method for relaxing nonholonomic constraints, to ensure that the skidding model remains susceptible to analysis using tools and techniques from classical optimal control theory. We refer to these relaxed constraints as ‘soft nonholonomic constraints’. This proposed methodology is the first approach that eliminates chattering by addressing its root cause, namely the order of the singular segments of the optimal control solution.
Salah Bazzi is a Postdoctoral Research Associate in the Action Lab at Northeastern University. He obtained his PhD in Mechanical Engineering from the American University of Beirut in May 2017. His research interests are robotic locomotion and manipulation, optimal control, nonlinear dynamics, nonholonomic mechanics, and human motor control and learning.