Robotics

Achieving reliable and real-time inverse kinematics (IK) for 6-degree-of-freedom (6-DoF) spherical-wrist manipulators remains a significant challenge. Analytical formulations often struggle with complex geometries and modeling errors, and standard numerical solvers (e.g., Levenberg–Marquardt) can stall near singularities or converge slowly. Purely data-driven approaches may require large networks and struggle with extrapolation. In this paper, we propose a low-latency, polynomial-based IK solution for spherical-wrist robots. The method leverages spherical coordinates and low-degree polynomial fits for the first three (positional) joints, coupled with a closed-form analytical solver for the final three (wrist) joints. An iterative partial-derivative refinement adjusts the polynomial-based angle estimates using spherical-coordinate errors, ensuring near-zero final error without requiring a full Jacobian matrix. The method systematically enumerates up to eight valid IK solutions per target pose. Our experiments against Levenberg–Marquardt, damped least-squares, and an fmincon baseline show an approximate 8.1× speedup over fmincon while retaining higher accuracy and multi-branch coverage. Future extensions include enhancing robustness through uncertainty propagation, adapting the approach to non-spherical wrists, and developing criteria-based automatic solution-branch selection.

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The exoskeleton rehabilitation robot is a structural robot that uses the actuator to control, so as to construct a human–robot collaborative rehabilitation training system to realize the perception and decoding of patients and promotes the recovery of limb function and neural remodeling. This review focused on the synergistic advancement of physical and information interaction in exoskeleton rehabilitation robotics. This review systematically retrieved literature related to the synergistic advancement of physical and information interaction in exoskeleton rehabilitation robotics. Publications from 2011 to 2025 were searched for across the EI, IEEE Xplore, PubMed, and Web of Science databases. The included studies mainly covered the period from 2018 to 2025, reflecting recent technological progress. This article summarizes the collaborative progress of physical and informational interaction in exoskeleton rehabilitation robots. The physical and information interaction is manifested in the bionic structure, physiological information detection and information processing technology to identify human movement intention. The bionic structural design is fundamental to realize natural coordination between human and robot to improve the following of movements. The active participation and movement intention recognition accuracy are enhanced based on multimodal physiological signal detection and information processing technology, which provides a clear direction for the development of intelligent rehabilitation technology.