Rapid Transport of Suspended Payloads
The topic of composing inputs for systems with mechanical flexibility has received attention for many years. Two popular methods are (1) shaping a nominal trajectory by convolution with an impulse sequence which itself cancels the flexibility, and (2) trajectory parameter optimization using structured basis functions, e.g. bang-coast-bang. However, each of these methods deteriorates in a different way when the motion is rapid compared to the natural period of the flexibility. Motions synthesized using dynamic programming offer clear advantages in these situations: (1) the resulting motions are smoother than those using impulse-convolution, and (2) dynamic programming is deterministic and does not rely on a convex objective function like gradient-based parameter optimization. Examples of the shortcomings of impulse-convolution and parameter-optimization will be shown; then we present both simulation and experimental evaluation of rapid transport of a suspended object using a robot manipulator and a minimum-energy trajectory obtained by dynamic programming.