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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.
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Submitted on : Thursday, August 17, 2017 - 4:24:36 PM
Last modification on : Thursday, June 4, 2020 - 8:04:03 AM


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Pierre Besset, Richard Béarée. FIR filter-based online jerk-constrained trajectory generation. Control Engineering Practice, Elsevier, 2017, 66, pp.169-180. ⟨10.1016/j.conengprac.2017.06.015⟩. ⟨hal-01575057⟩



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