Trajectory planning for a manipulator with nonlinear Coulomb friction using a dynamically incremental genetic algorithm

Global warming and environmental destruction are caused in part by the mass consumption of energy by industries that use robotic manipulators. Hence, there is a need to minimize the energy used for manipulator control systems. It is relatively easy to analytically obtain an optimal solution for a linear system. However, a multi-link manipulator is governed by a nonlinear dynamical equation that is difficult to solve as a two-point boundary value problem. Here, the manipulator angles are approximated by Taylor and Fourier series, whose coefficients are sought by a genetic algorithm (GA) to optimize the objective function subject to the boundary conditions. A search method is proposed for planning the trajectory of a manipulator with nonlinear friction and geometrical constraints.