Trajectory Optimization of Continuum arm robots

Rigid manipulators are applicable for a very structured environment and standard applications. For real world applications, continuum manipulators are used which has required high degrees of freedom, and compliance. The current work focus on the trajectory optimization of continuum robot for a specified application to minimize energy usage. To achieve this task Lagrangian mechanics is used to develop the mathematical model of the continuum robot with the payload. In this case the trajectory optimization has been carried out by treating the problem as a nested optimization problem. The outer optimization task is to optimize the trajectory using minimization of input force as primary goal where initial and final configurations of the arm are already available. Here, Genetic Algorithm is used as the optimizer for the selected tasks. The purpose of inner optimization loop is to find the feasible inverse solution for the manipulator that is required to calculate input forces which is further required to optimize the trajectory of the arm. A constrained non-linear optimization algorithm is used for the task. The optimization results show 30-80 % decrease in the input force required for the specified trajectories of the arm. The current paper shows that various tasks can be optimized using the formulated strategy to save the energy required by the arm to execute specified task.