Although many studies exist on mobile robot path planning, the disadvantages of complex algorithms and many path nodes in logistics warehouses and manufacturing workshops are obvious, mainly due to the inconsistency of map environment construction and pathfinding strategies. In this study, to improve the efficiency of mobile robot path planning, the Delaunay triangulation algorithm was used to process complex obstacles and generate Voronoi points as pathfinding priority nodes. The concept of the grid was used to extract obstacle edges to provide obstacle avoidance strategies for robot pathfinding. Subsequently, the search for priority and regular path nodes used the improved A-star (A*) algorithm. The dynamic fusion pathfinding algorithm (DFPA), based on Delaunay triangulation and improved A*, was designed, which realizes the path planning of mobile robots. MATLAB 2016a was used as the simulation software, to firstly verify the correctness of the DFPA, and then to compare the algorithm with other methods. The results show that under the experimental environment with the same start point, goal point, and number of obstacles, the map construction method and pathfinding strategy proposed in this paper reduce the planned path length of the mobile robot, the number of path nodes, and the cost of overall turn consumption, and increase the success rate of obtaining a path. The new dynamic map construction method and pathfinding strategy have important reference significance for processing chaotic maps, promoting intelligent navigation, and site selection planning.

To address the lightweight and real-time issues of coal sorting detection, an intelligent detection method for coal and gangue, Our-v8, was proposed based on improved YOLOv8. Images of coal and gangue with different densities under two diverse lighting environments were collected. Then the Laplacian image enhancement algorithm was proposed to improve the training data quality, sharpening contours and boosting feature extraction; the CBAM attention mechanism was introduced to prioritize crucial features, enhancing more accurate feature extraction ability; and the EIOU loss function was added to refine box regression, further improving detection accuracy. The experimental results showed that Our-v8 for detecting coal and gangue in a halogen lamp lighting environment achieved excellent performance with a mean average precision (mAP) of 99.5%, was lightweight with FLOPs of 29.7, Param of 12.8, and a size of only 22.1 MB. Additionally, Our-v8 can provide accurate location information for coal and gangue, making it ideal for real-time coal sorting applications.

The new method of rock breaking based on the combination of circular sawblade and conical pick was proposed to improve the effectiveness of hard rock breaking. The numerical simulation method was applied to research the conical pick cutting arc rock plate by ANSYS/LS‐DYNA. The conical pick cutting arc rock plate numerical simulation model was established to research the influence of arc rock plate structural parameters and cutting parameters on cracks formation and propagation of the arc rock plate and the cutting force in the process of conical pick cutting arc rock plate. The amount of cracks is positively correlated with arc rock plate thickness, the cutting speed, and distance of cutting point to arc rock plate central axis and negatively correlated with the cutting angle. The mean peak cutting force is positively correlated with the thickness of arc rock plate and the distance of cutting point to arc rock plate central axis; however, it is negatively correlated with the arc rock plate height and width and cutting angle of conical pick. The simulation results can be used to predict the conical pick work performance with various cutting parameters and structural parameters.

Although state-feedback optimal control of the continuous-time (CT) systems has been extensively studied, resolving optimal control online via output-feedback is still challenging, especially only input-output information can be used. In this paper, we develop an innovative technique to online design the output-feedback optimal control (OFOC) of the CT systems. Firstly, to synthesis the OFOC, an output-feedback algebraic Riccati equation (OARE) is constructed, which can be solved using input-output information. Then, an online policy learning (PL) algorithm is developed to compute the solution of the OARE, where only the input-output information is required and the conventional offline learning procedure is avoided. Simulations based on an aircraft model are provided to test the developed control method and online learning algorithm.

Fused deposition modeling (FDM) has been one of the most widely used rapid prototyping (RP) technologies leading to the increase in market attention. Obviously it is desirable to print 3D objects; however, existing FDM printers are restricted to printing only monochrome objects because of the entry-level nozzle structure, and literature on the topic is also sparse. In this paper, the CAD model of the nozzle is established first by UG (Unigraphics NX) software to show the structure of fused deposition modeling 3D printer nozzle for color mixing. Second, the flow channel model of the nozzle is extracted and simplified. Then, the CAD and finite element model are established by UG and ICEM CFD software, respectively, to prepare for the simulation. The flow field is simulated by Fluent software. The nozzle’s suitable temperature at different extrusion speeds is obtained, and the reason for the blockage at the intersection of the heating block is revealed. Finally, test verification of the nozzle is performed, which can produce mixed-color artifacts stably.

Hydraulic support is an indispensable equipment for coal mining face. To detect the position and posture of the hydraulic support and automatically control its straightness at the mining working face, we developed a device based on the principle that three noncolinear points determine a plane and proposed a novel method using it. First, the sensor parameters in the device were experimentally calibrated. Second, the accuracy of the device was evaluated in the single point detection experiment by measuring the position of the nine datum points. Through actual testing, our detection accuracy can reach 24.82mm. Third, our method was validated in the experiment of the plane detection. Finally, the detection device was installed on the hydraulic support mode. The change of the position and posture of the canopy in the movement of the hydraulic support lifting leg, realized the detection of position and posture of the adjacent hydraulic support, and the feasibility of the detection method was verified. Our research on the position and posture detection of the hydraulic support can lay an important theoretical foundation for the automatic control of the straightness of mining working face and the surveillance of the dangerous posture of the hydraulic support. Furthermore, it can provide a novel monitoring approach for preventing collapse of hydraulic supports under complex geological conditions such as large dip angles and large mining heights.