<p>An XG822-EL excavator is transformed into a manipulator with redundant degree-of-freedom (DOF). To achieve high-quality, high-efficiency, and low-impact operations, an optimization model based on joint motion time and impact optimization is proposed for joint motion planning, which can realize the optimal constraints of motion time-impact on the premise of ensuring joint response errors. The trajectory planning and tracking test platform of the redundant DOF manipulator are constructed, and joint motion optimization and the trajectory tracking control tests of the manipulator test the tracking error, movement time, maximum acceleration, and impact amplitude of the joint and end. Experiments show that the system has a good response speed and accurately tracks the corresponding motion trajectory with a maximum error of the joint near the target point less than 0.1°. The experiment also proves the effectiveness of the optimization model, which balances the movement time and movement impact by adjusting the planning parameters.</p>

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Research on motion planning and tracking control of a redundant degree-of-freedom manipulator

  • Guangjun Liu,
  • Ziwei Wang,
  • Gaoyang Wu

摘要

An XG822-EL excavator is transformed into a manipulator with redundant degree-of-freedom (DOF). To achieve high-quality, high-efficiency, and low-impact operations, an optimization model based on joint motion time and impact optimization is proposed for joint motion planning, which can realize the optimal constraints of motion time-impact on the premise of ensuring joint response errors. The trajectory planning and tracking test platform of the redundant DOF manipulator are constructed, and joint motion optimization and the trajectory tracking control tests of the manipulator test the tracking error, movement time, maximum acceleration, and impact amplitude of the joint and end. Experiments show that the system has a good response speed and accurately tracks the corresponding motion trajectory with a maximum error of the joint near the target point less than 0.1°. The experiment also proves the effectiveness of the optimization model, which balances the movement time and movement impact by adjusting the planning parameters.