Time-optimal trajectory planning for hyper-redundant manipulators in 3D workspaces

A novel approach is proposed for time-optimal trajectory planning of a hyper-redundant manipulator which is requested to move from an initial configuration to a final configuration in 3D workspaces. The 3D workspace is cluttered with static objects which have known geometry and position. The proposed approach generates a trajectory for the manipulator's end-effector considering simultaneously the kinematical constraints of the manipulator (specifically velocity and acceleration) and the presence of obstacles. The method solves an optimization problem to find the minimum time trajectory to perform the requested tasks. The optimization problem is solved by using a Genetic Algorithm with multiple population. The efficiency of the developed method is investigated and discussed through characteristic simulated experiments concerning a variety of operating environments.