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February 5, 2026Robotics0 citationsOpen Access

Extended Operational Space Kinematics, Dynamics, and Control of Redundant Non-Serial Compound Robotic Manipulators

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EHEdward J. HaugJBJames Brandt

Key Points

  • To develop a comprehensive framework for controlling redundant non-serial robotic manipulators using advanced kinematic and dynamic models.
  • Developed a differential-geometry-based, multi-valued inverse kinematic mapping.
  • Formulated coupled second-order ordinary differential equations for dynamics.
  • Integrated system dynamics with control strategies like model predictive control.
  • Validated methods through simulation of a material loader manipulator.
  • Demonstrated advantages in generality and numerical accuracy.
  • Achieved smoother trajectories during manipulation.
  • Successfully maintained task constraints during operation.

Abstract

An extended operational space kinematics and dynamics formulation is presented for the control of redundant non-serial compound robotic manipulators. A broad spectrum of high-load-capacity non-serial manipulators used in earth moving, material handling, and construction applications is addressed. Departing from conventional approaches that rely on Jacobian pseudoinverses and local null-space projections, a globally valid, differential-geometry-based, multi-valued inverse kinematic mapping is defined at the configuration level, with the explicit self-motion parameterization of manipulator redundancy. The formulation yields coupled second-order ordinary differential equations of manipulator dynamics on the product space of task variables and self-motion coordinates. This enables the direct integration of system dynamics with control strategies, such as model predictive control or feedback design, while maintaining task constraint compliance. The methods presented are validated through the simulation and control of a non-serial compound material loader manipulator with multiple degrees of redundancy, demonstrating advantages in generality, numerical accuracy, and trajectory smoothness.

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Cite This Study

Haug et al. (2026) studied this question.

synapsesocial.com/papers/6984343ff1d9ada3c1fb23b9https://doi.org/10.3390/robotics15020034
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