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An Error-Adaptive Competition-Based Inverse Kinematics Approach for Bimanual Trajectory Tracking of Humanoid

Jiaxiu Liu1, Zijian Wang1, Hongfu Tang1

  • 1School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150080, China.

Biomimetics (Basel, Switzerland)
|April 27, 2026
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Summary

This study introduces an efficient error-adaptive competition-based inverse kinematics (EAC-IK) method for humanoid robots. The EAC-IK approach improves bimanual trajectory tracking accuracy and computational efficiency.

Keywords:
humanoid upper-limb robotinverse kinematicsmotion planningtrajectory tracking

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Area of Science:

  • Biomimetic Robotics
  • Robotics Control Systems
  • Humanoid Robot Kinematics

Background:

  • Humanoid upper-limb robots require sophisticated inverse kinematics for human-like movements.
  • Existing methods for bimanual trajectory tracking face challenges with computational load and synchronization accuracy.

Purpose of the Study:

  • To develop an efficient inverse kinematics approach for bimanual trajectory tracking in humanoid robots.
  • To enhance coordination and reduce computational complexity in robotic upper-limb operations.

Main Methods:

  • Proposed an error-adaptive competition-based inverse kinematics (EAC-IK) approach.
  • Unified modeling of absolute and synchronization errors, reformulating end-effector constraints.
  • Implemented an error-adaptive competition mechanism for online weight regulation.
  • Introduced a virtual second-order command shaper for joint trajectory reconstruction.

Main Results:

  • The EAC-IK method demonstrated lower tracking and synchronization errors compared to zeroing neural-network-based methods.
  • Achieved significant reductions in left-arm position (from 1.60×10⁻³m to 0.70×10⁻³m) and orientation (from 4.72×10⁻³rad to 0.95×10⁻³rad) errors.
  • Reduced synchronization error from 1.96×10⁻³ to 1.30×10⁻³.
  • Improved computational efficiency with an average runtime decrease from 0.82ms to 0.63ms.

Conclusions:

  • The proposed EAC-IK method offers superior performance in terms of accuracy and efficiency for bimanual trajectory tracking.
  • The approach effectively addresses the limitations of existing inverse kinematics methods for humanoid robots.
  • Validated through simulations and experiments on a hyper-redundant humanoid upper-limb robot.