ROSep 14, 2019

Planning Jerk-Optimized Trajectory with Discrete-Time Constraints for Redundant Robots

arXiv:1909.06570v259 citations
Originality Synthesis-oriented
AI Analysis

This addresses motion planning for redundant robots in manufacturing to enhance fabrication quality, but it appears incremental as it builds on existing trajectory optimization methods.

The paper tackles the problem of planning motion trajectories for redundant robots in manufacturing, where complex tool-paths involve many discrete-time constraints, and it optimizes jerk to improve fabrication quality, though no concrete numbers are provided.

We present a method for effectively planning the motion trajectory of robots in manufacturing tasks, the tool-paths of which are usually complex and have a large number of discrete-time constraints as waypoints. Kinematic redundancy also exists in these robotic systems. The jerk of motion is optimized in our trajectory planning method at the meanwhile of fabrication process to improve the quality of fabrication.

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