Journal of Applied Science and Engineering

Published by Tamkang University Press

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A Composite Objective-Driven Framework for High Performance Robotic Trajectory Optimization

 2026

 Volume 32

Qi Yang, Dongwei Li, Xin Zhang, Xinyu Cai, and Shengbing Sun

School of Mechanical Engineering, Shenyang Ligong University, Shenyang, Liaoning,China

Received: March 2, 2026
Accepted: March 18, 2026
Publication Date: April 25, 2026

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Overall Performance Radar Chart 

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In high-precision robotic tasks, achieving optimal trajectory smoothness and dynamic performance is a critical challenge. Traditional integer-order optimization methods often fail to accurately capture intrinsic nonlinear dynamics and long-term memory effects, creating a performance bottleneck. To overcome these limitations, this paper proposes a novel framework: Composite Fractional Objective for Trajectory Optimization (CFOTO). By integrating fractional calculus theory, we construct a composite objective function that incorporates both a fractional norm and a fractional-order smoothness term, which is solved using the fmincon solver. Extensive comparative simulations benchmark CFOTO against three classical and state-of-the-art planning methods. The results demonstrate that CFOTO achieves superior overall performance, exhibiting distinct advantages in trajectory smoothness and algorithmic convergence speed. This research provides a high-performance solution for robotic trajectory planning and offers practical evidence for applying fractional calculus in intelligent control.

Keywords: Trajectory Planning, Fractional Calculus, Nonlinear Optimization, Robotic Manipulator, Smoothness

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