What question did this study set out to answer?

To develop an automated trajectory planning framework for robotic manipulators that maximizes execution efficiency while minimizing mechanical shock and vibration.

July 3, 2023ElectronicsOpen Access

Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint

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To develop an automated trajectory planning framework for robotic manipulators that maximizes execution efficiency while minimizing mechanical shock and vibration.
Formulated path sequencing as a travelling salesman problem solved via an improved ant colony algorithm combined with high-order spline interpolation.
Implemented automatic trajectory generation using nearest start point selection instead of manual configuration.
Evaluated the optimization strategy across Cartesian and joint space coordinates using numerical simulations and physical manipulator experiments.
Optimized the free-load motion sequence to achieve the shortest transit path, boosting manipulator operational efficiency by nearly 65%.
Produced smooth interpolated trajectories across both Cartesian and joint spaces, substantially reducing mechanical shocks and vibrations.

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Implication

Experimental validation demonstrates a 65% efficiency gain in robotic manipulators, suggesting faster and smoother automated manufacturing paths.

Cite This Study

Xu et al. (2023) studied this question.

synapsesocial.com/papers/6a72e5a90659c579cd60d589 https://doi.org/10.3390/electronics12132928

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Implication

Experimental validation demonstrates a 65% efficiency gain in robotic manipulators, suggesting faster and smoother automated manufacturing paths.

Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint

Key Points

Discussion

Implication

Cite This Study

Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint

Key Points

Discussion

Implication

Cite This Study

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