Planning trigonometric frequency central pattern generator trajectory for cyclic tasks of robot manipulators

Planning efficient trajectories is an essential task in most automated robotic applications. The execution time and smoothness are usually important considerations for economic and safety reasons. A novel method to generate a trigonometric frequency central pattern generator trajectory is presented in this paper for cyclic point-to-point tasks of industrial robotic manipulators. The proposed method is biologically motivated by the concept of central pattern generator, which is a special neural circuit underlying most rhythmic activities in living beings. A modified central pattern generator model with simple network structure is developed for yielding the desired joint trajectories of robots. An important property of this technique lies in the fact that stable online trajectory transition between different paths is enabled by simply adjusting the central pattern generator control parameters. Moreover, kinematic constraints of the robot can be taken into account for optimizing the robot motion instead of setting a priori the execution time. Two examples of the pick-and-place operation, which is a typical cyclic point-to-point task, are used to illustrate the validity of the method. The results of simulation indicate that the proposed method is capable of producing smooth and time-optimal trajectories, which have also been compared with those yielded by other trajectory planning approaches found in the scientific literature