Structural design and intelligent control of a self-reconfigurable robot for space cabins

With the growing volume and complexity of crewed space missions, astronauts face heavy workloads and safety risks when performing inspection, logistics, and experimental operations inside confined space station cabins. To address this, we propose a spherical modular self-reconfigurable free-flying robot specifically designed for micro-gravity cabins. Guided by TRIZ theory, a compact mechanical architecture is developed that reconciles the contradictions among thrust, docking precision, and volume constraints. The robot employs six orthogonally arranged ducted-fan thrusters for full six-degree-of-freedom maneuvering and a hybrid mechanical–electromagnetic docking mechanism that enables reliable multi-robot assembly within large pose and position tolerances. A unified Lagrangian model is then established for both the free-flying platform and the post-reconfiguration multi-body system with an attached manipulator. To cope with nonlinear, strongly coupled dynamics and parameter uncertainties, a T–S fuzzy neural network PID controller is designed to realize on-line tuning of PID gains. Comparative simulations with classical PID and fuzzy-PID schemes show that the proposed controller significantly shortens settling time, reduces overshoot, and improves steady-state accuracy, verifying the effectiveness and robustness of the overall structural design and control framework for intra-vehicular service robots.