Optimization of manipulator point to point motion considering actuator output capability constraints

An optimization algorithm for planning minimum time cubic polynomial joint trajectory splines, is presented. In this optimization, constraints on manipulator joint kinematics and actuator output capabilities are enforced. The contribution of this paper to the algorithm is the incorporation of the actuator capability constraints in the optimization.

Manipulator tasks are specified as a sequence of required end effector locations and orientations, (task spaces). Continuous motion through the task spaces is achieved through use of cubic polynomial trajectory splines at the joint level. Movement times between task spaces are optimized off-line, using a direct search technique. Enforcement of the joint constraints is achieved by scaling infeasible manipulation kinematics and dynamics through expansion of the total motion time.

Example optimizations are included. It was found that trajectory optimization considering kinematic and dynamic constraints, will produce results superior to simple time scaling of a dynamically infeasible, kinematic optimum trajectory.