A CPG-based online trajectory planning method for industrial manipulators

Abstract

Trajectory planning plays an important role in task operations of industrial robots. A novel online method for generating rhythmic Point-to-Point (PTP) trajectories is presented in this paper to meet the requirements of smoothness and online trajectory transition for repetitive PTP tasks of industrial manipulators. This method is inspired by the biological concept of Central Pattern Generator (CPG), which underlies most rhythmic activities in animal bodies. A modified CPG model with simple structure is designed based on traditional harmonic trajectory for producing the desired joint angles of robots. The pick-and-place task, as a representative example of PTP operations, is used to demonstrate the effectiveness of the novel method. The simulation results show that the method is capable of generating smooth trajectory in Cartesian space without any other additional restrictive conditions while only requires solving the inverse kinematics of the initial and final points. Furthermore, it enables stable online trajectory transition with jerk constraints by simply modulating the CPG parameters, which reduces the operation time and is beneficial to increasing the productive efficiency.