Wheel loaders play a crucial role in daily production and transportation. With the rapid development of intelligence in passenger vehicles, freeing loader operators from high-risk and repetitive tasks has become a pressing issue. This paper presents a novel and efficient path planning and tracking framework tailored to the unique body structure and specific operating environment of loaders. We improve the Hybrid A* search algorithm based on the operational characteristics of loaders and integrate it with dynamically updated grid maps to enable the autonomous planning of loader operating paths in unstructured environments, meeting the efficiency requirements of production. Additionally, to address the challenge of poor trajectory tracking control accuracy caused by hydraulic articulated steering, we propose a new loader trajectory tracking controller based on the idea of hierarchical control. We use an extended state observer to compensate for unknown disturbances in the steering execution layer and employ fuzzy fractional-order PID to handle the nonlinearity of loaders. Field experiments using the proposed approach demonstrate that loaders can autonomously and in real-time complete tasks in dynamically changing operating scenarios.

The error motion of the precision rotary stage, particularly the tilt error motion, significantly influences the accuracy of machining and measuring equipment. Nonetheless, reliable and effective in situ measurement methods for tilt error motion are still limited. Based on the analysis of the conventional three-probe measurement method, this paper proposes a multi-probe measurement method using an ultra-precision reference plate with high-resolution displacement sensors. This method employs principles and methods to avoid harmonic suppression issues through optimal probe designs, enabling simultaneous quantification of tilt and axial error motions via error separation. Error separation techniques can effectively decouple motion errors from artifact form error, making them widely applicable in precision measurement data processing. Experimental validation confirmed that the synchronous measurement error is not greater than 4.69%, consequently affirming the metrological efficacy and reliability of the method. This study provides an effective method for real-time error characterization of rotary stages.

The rotational error motion of precision aerostatic rotary stages substantially affects the accuracy of machining and measuring equipment. A comprehensive and flexible error modeling method is absent. This paper develops an analytical model for the error motion of an aerostatic rotary stage bearing, utilizing linear superposition and spatial force equilibrium principles. The error motion of an orifice-restricted rotary stage is computed using this approach. The impact of bearing manufacturing inaccuracies (e.g., journal roundness, thrust plate profile) and micro-vibrations caused by internal turbulence is analyzed. Finally, the model was validated experimentally using the reversal method. The results indicate that bearing manufacturing errors positively correlate with error motion, and micro-vibration considerably influences errors at the sub-100 nm level. The relative error between the predicted and measured values is less than 15%, confirming the validity and applicability of this modeling and analytical approach. This research enhances error motion analysis methods and offers a novel constructive reference for predicting and optimizing error motion in precision aerostatic rotary stages.