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A Cartesian-Based Trajectory Optimization with Jerk Constraints for a Robot.

Zhiwei Fan1,2,3, Kai Jia1,2,4, Lei Zhang1,2,4

  • 1State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.

Entropy (Basel, Switzerland)
|May 16, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel time-optimal path-parameterization (TOPP) algorithm for robotic trajectory planning. The method efficiently handles joint jerk constraints, enabling faster and smoother robot movements.

Keywords:
iterative optimizationjerk limitsphase planetime-optimal path parameterizationtime-optimal trajectory planning

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Area of Science:

  • Robotics
  • Control Theory
  • Optimization

Background:

  • Trajectory planning is crucial for robot efficiency.
  • Joint jerk constraints are essential for smooth and safe robot motion.
  • Existing methods struggle with complex constraints in Cartesian space.

Purpose of the Study:

  • To develop an effective algorithm for time-optimal trajectory planning (TOTP) with joint jerk constraints.
  • To address challenges in parameterizing paths in Cartesian space while respecting joint-space constraints.
  • To provide an efficient computational solution for optimal control problems in robotics.

Main Methods:

  • Proposed a time-optimal path-parameterization (TOPP) algorithm.
  • Utilized nonlinear optimization and an iterative optimization framework.
  • Formulated the problem in the (s,s˙)-phase plane to solve the optimal control problem (OCP).

Main Results:

  • The TOPP algorithm effectively addresses time-optimal trajectory planning with joint jerk limits.
  • Demonstrated the ability to satisfy third-order constraints in joint space within a Cartesian framework.
  • Showcased an efficient computational solution for nonlinear constraints in trajectory optimization.

Conclusions:

  • The developed TOPP algorithm is a viable solution for time-optimal trajectory planning under joint jerk constraints.
  • The approach is applicable to a diverse range of robotic systems.
  • This method enhances the efficiency and smoothness of robotic motion planning.