Accurate and efficient manufacturing of large-scale structures is an important and challenging issue. To this end, a mobile hybrid robot named CraftsRobot is designed and developed for in-situ machining the local features of large-scale structures. The mobile hybrid robot comprises a mobile vehicle, a guide rail, a two degree-of-freedom (DoF) mechanical arm, and a five-DoF light-weight parallel module. The interaction mechanism between the parallel module and the mechanical arm is disclosed to build the error prediction model. On this basis, a model predictive compensation method is proposed. In each servo cycle, the command pose of the parallel module is modified and under the effect of the interaction-induced error superimposed on the modified command pose, the parallel module will reach the target pose. The results of simulation and experiment both verify the effectiveness of the compensation model. After compensation, the mobile hybrid robot is applied to machine the features on a typical large-scale structure and the machining errors are within 0.04 mm. The experimental results show that the designed robot can machine local features of large-scale structures in situ and meet the precision requirements. Together, this study provides a novel approach to achieve accurate and efficient manufacturing of large-scale structures.

Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model’s potential to transform open-pit mining operations by using intelligent planning.

Calibration is an efficient approach to improve the position accuracy of robots. But in some industrial practice, only part of the DH parameters can be compensated and the reduction ratios of reduction boxes and coupling coefficient of fifth joint and sixth joint are not originally accurate in the robot CNC system. If all DH parameters are identified and only part of them is compensated, and the reduction ratio errors and coupling coefficient error are ignored, the position error may be large. In this paper, based on the robot CNC system, a calibration method for identifying the reduction ratios, coupling coefficient and part of the DH parameters is proposed. This method can improve the position accuracy as much as possible by compensating above identified parameters in CNC system. RB08 robot and Leica laser tracker are used to conduct the experiment. Results show that the maximum/mean position errors are developed from 58.292mm/36.780mm to 0.496mm/0.331mm. Therefore, this calibration method is effective and can be applied in practical industrial productions.

3-PP(Pa)S robot is a six degrees of freedom (DOFs) parallel mechanism with 2-DOF active planar joint. For the design and application of the 3-PP(Pa)S robot, it is essential to investigate the motion/force transmissibility of the robot. But previous studies of the motion/force transmissibility have mainly focused on the parallel robots with 1-DOF active joints and thus cannot be directly applied to the 3-PP(Pa)S robot. In this paper, input twist subspace, transmission wrench subspace and output twist subspace are investigated to build mathematical models of the twists and wrenches corresponding to the 2-DOF active planar joint. Afterwards, based on the previous established frame of the local transmission index, some extended performance evaluation indices are defined to describe the motion/force transmissibility of the 3-PP(Pa)S robot. On this basis, the singularity and motion/force transmissibility of this mechanism are investigated. The motion/force transmissibility evaluation method is meaningful and applicable for the 3-PP(Pa)S parallel robot with 2-DOF active joints and can be further applied to other mechanisms with multi-DOF active joints.