148. trajectory optimization of 7-dof baxter robot's arm
Name: Mostafa Bagheri
Grad Year: 2019
We present nonlinear analytical coupled trajectory optimization of a 7-DOF Baxter manipulator validated through experimental work utilizing global optimization tools and extremum seeking method. The robotic manipulators used in network-based applications of industrial units and even homes, for disabled patients, spend signiﬁcant lumped amount of energy and therefore, optimal trajectories need to be generated to address efﬁciency issues. We here utilize extremum seeking method alongside with heuristic (Genetics) and gradient-based (GlobalSearch) algorithms to avoid being trapped in several possible local minima, enforcing geometrical constraints in order to minimize the lumped amount of energy consumed in a nominal path given. Note that such robots are typically operated for thousands of cycles resulting in a considerable cost of operation. Due to the expected computational cost of such global optimization algorithms, step size analysis is carried out to minimize both the computational cost (iteration) and possibly cost function by ﬁnding an optimal step size. Global design sensitivity analysis is also performed to examine the effects of changes of optimization variables on the cost function deﬁned.
Industry Application Area(s)
Control Systems | Energy/Clean technology