FIR filter-based online jerk-constrained trajectory generation

Abstract

In the context of human-robot manipulation interaction for service or industrial robotics, the robot controller must be able to quickly react to unpredictable events in dynamic environments. In this paper, a FIR filter-based trajectory generation methodology is presented, combining the simplicity of the analytic second-order trajectory generation, i.e. acceleration-limited trajectory, with the flexibility and computational efficiency of FIR filtering, to generate on the fly smooth jerk-constrained trajectories. The proposed methodology can generate synchronized (fixed-time) and time-optimal jerk-limited trajectories from arbitrary initial velocity and acceleration conditions within 20 microsecond. Other jerk-constrained trajectories such as jerk-time fixed trajectories, which are particularly suitable for vibration reduction, can be easily generated. Experimental validations carried out on a seven axis Kuka LBR iiwa are presented.