Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System

Unmanned Aerial Vehicles(UAVs) are attaining more and more maneuverability and sensory ability as a promising teleoperation platform for intelligent interaction with the environments. This work presents a novel 5-degree-of-freedom (DoF) unmanned aerial vehicle (UAV) cyber-physical system for aerial manipulation. This UAV's body is capable of exerting powerful propulsion force in the longitudinal direction, decoupling the translational dynamics and the rotational dynamics on the longitudinal plane. A high-level impedance control law is proposed to drive the vehicle for trajectory tracking and interaction with the environments. In addition, a vision-based real-time target identification and tracking method integrating a YOLO v3 real-time object detector with feature tracking, and morphological operations is proposed to be implemented onboard the vehicle with support of model compression techniques to eliminate latency caused by video wireless transmission and heavy computation burden on traditional teleoperation platforms.Comment: Newsletter of IEEE Technical Committee on Cyber-Physical System

Negative obstacle detection on open pit roads based on multi-feature fusion

With the gradual implementation of intelligent mine concept, intelligence and unmanned operation are gradually implemented in mining area. Unmanned driving of open pit mine trucks is increasingly becoming the main focus of intelligent mine construction. In order to solve the safety problems of the overturn of unmanned vehicles and heavy-duty trucks due to irregular negative obstacles appearing in some parts of road surface such as potholes and collapses in open pit mines, and to improve the safe driving coefficient in mines, a multi-feature fusion method of detecting negative obstacles in open pit mine roads is proposed. The method uses the BiFPN feature fusion module to improve the weight proportion of small-scale negative obstacle detection, introduces the spatial and channel dual attention mechanism to improve the feature extraction and feature fusion ability of negative obstacle edges, so as to improve the detection accuracy of small-scale negative obstacles on the road. Also, the SIoU Loss is adopted as the loss function of the model bounding box, the Anchor by using the K-means++ method is used to improve the convergence speed and boundary frame localization effect of the obstacle detection model, the hyperparameters are optimized based on genetic algorithm to make the model more suitable for the mine scene, and finally the fast and accurate recognition of negative obstacles on the mine road is realized. The experiments show that the detection model can quickly and accurately identify the negative road obstacle targets in the complex background of the open pit mine, and the detection accuracy, recall rate, and mAP of the negative road obstacle targets reach 96.9%, 89.9%, and 95.3%, respectively, and the size of the model is only 12.7 MB. Compared with other mainstream detection networks, the network model is more suitable for the safety needs of unstructured road driving in open pit mining areas under complex environment, and the robustness of the detection model is good, which can be adapted to a variety of situations in open pit mining areas, providing a feasible method for the detection of negative obstacles on unstructured roads in open pit mining areas where the actual environment is complex and variable, and providing some safety warnings for the safety of unmanned trucks in open pit mines

Comparative transcriptome analyses of immune responses to LPS in peripheral blood mononuclear cells from the giant panda, human, mouse, and monkey

Gram-negative bacteria are major pathogens that can cause illnesses in giant pandas. Lipopolysaccharides (LPS), components of Gram-negative bacteria, can activate immune responses in mammals (i.e., humans and mice) through recognition by toll-like receptors (TLRs). However, the giant pandas’ immune response to LPS stimulation and the differences between the giant panda and other mammals are not fully known. In this study, we administrated peripheral blood mononuclear cells (PBMCs) from giant pandas, humans, C57BL/6 mice, and rhesus monkeys by LPS treatment at 6 h followed by RNA sequencing (RNA-seq), respectively, with control of non-stimulation. KEGG analyses of differentially expressed genes (DEGs) pathways indicated that LPS could activate the classic signaling pathway of NF-κB in PBMCs from those four tested species. Thus, similar to the other three species, NF-κB is an LPS-responsive regulator of innate immune responses in giant pandas. Furthermore, the expression patterns of adapter genes, inflammatory cytokine genes, chemokines, interferon genes, cytokine genes related to cell growth and development, costimulatory molecules, Th1/Th2 cytokine genes, Th17 cytokine genes, Th9, and Th22 cytokine genes were compared among giant pandas and three other species. Our data indicated that in addition to the similar expression patterns of certain genes among giant pandas and other species, the unique expression pattern response to LPS in giant pandas was also discovered. Furthermore, Th9, Th17, and Th22 cells might be involved in the response to LPS in giant pandas at this tested time point. This study reveals that LPS-induced immune responses have different sensitivities and response timelines in giant pandas compared with other mammals. This study facilitates further understanding of the role of the TLR signaling pathway and the immune system in giant pandas, which might be helpful for disease prevention and protection

Heat Treatment and Ventilation Optimization in a Deep Mine

In order to address the issue of high temperatures and thermal damages in deep mines, the factors causing downhole heat damage at high temperatures were analyzed, the mine ventilation system was optimized and rebuilt, and a cooling system was established. The proposed cooling system uses mine water as the cooling source, and its features are based on the analysis of traditional cooling systems. The current ventilation system in the 1118 m deep pit of the Jinqu Gold Mine was evaluated, and the ventilation network, ventilation equipment, and ventilation structures near the underground working face were optimized. The low-temperature mine water stored in the middle section of the mine at 640 m depth was used as the cooling source, and a cooling system was established near the 440 m deep middle return well to alleviate the high-temperature and high-humidity conditions of the 280 m deep middle-western area. The results show that the effective air volume in the west wing at 280 m was 3.0 m3/s, the operating ambient temperature was 27.6°C, the relative humidity was reduced to 76%, and the temperature was reduced by 5-6°C after the optimization of the system

A high-precision positioning method for open-pit mine vehicles based on improved HMM deviation correction algorithm

Vehicle location deviation could easily occur in complex road network of open-pit mines, which seriously affect production vehicle route planning and intelligent scheduling.In this light, this study proposed a method for high-precision positioning and rectification of open pit minecars based on an improved HMM(Hiddden Markov Model).Specifically, this study clipped the road section by the complex road network map of the constructed open-pit mine, and cleaned the positioning trajectory data of the minecart, whose density was sparsed and segmented; a buffer zone was established to search for candidate road points of the trajectory, so as to improve the efficiency of the minecart positioning and correction under the complex road network; the HMM optimization model of positioning deviation correction was established by calculating the positioning observation probability and transition probability of the minecart.The optimal deviation correctionwas conducted in combination with the Viterbi algorithm to achieve high-precision positioning and deviation correction of the open-pit minecart.Results indicate that the method produces a better correction effect than the original HMM positioning correction method, the correction accuracy can reach 89.2 %, and the average correction time is only 0.055 s.This could effectively correct the positioning coordinates of open-pit mine vehicles under complex backgrounds

A Real-Time Negative Obstacle Detection Method for Autonomous Trucks in Open-Pit Mines

Negative obstacles such as potholes and road collapses on unstructured roads in open-pit mining areas seriously affect the safe transportation of autonomous trucks. In this paper, we propose a real-time negative obstacle detection method for self-driving trucks in open-pit mines. By analyzing the characteristics of road negative obstacles in open-pit mines, a real-time target detection model based on the Yolov4 network was built. It uses RepVGG as the backbone feature extraction network, applying SimAM space and a channel attention mechanism to negative obstacle multiscale feature fusion. In addition, the classification and prediction modules of the network are optimized to improve the accuracy with which it detects negative obstacle targets. A non-maximum suppression optimization algorithm (CIoU Soft Non-Maximum Suppression, CS-NMS) is proposed in the post-processing stage of negative obstacle detection. The CS-NMS calculates the confidence of each detection frame with weighted optimization to solve the problems of encountering obscure negative obstacles or poor positioning accuracy of the detection boxes. The experimental results show that this research method achieves 96.35% mAP for detecting negative obstacles on mining roads with a real-time detection speed of 69.3 fps, and that it can effectively identify negative obstacles on unstructured roads in open-pit mines with complex backgrounds

Study on Blasting Effect Optimization to Promote Sustainable Mining under Frozen Conditions

In order to respond to the theme of national green and healthy sustainable development and in response to the problems of large block rates and pollution of the environment after the blast mining of underground rocks in alpine areas, we conducted research on the joints of underground rocks and the blastability of frozen rocks. According to the actual geological conditions of an underground mine blasting in Heilongjiang Province, three kinds of joint blasting geometric models were established. The rock mass blasting process of different types of joints was simulated by LS-DYNA software and the influence law of joints on rock mass blasting was summarized. The blasting crater test and the triaxial compression test of frozen rock were carried out. Combined with the blasting fragmentation characterization function (R-R and G-G-S), the blasting fragmentation, strength and stiffness of frozen rock at different temperatures were obtained. Based on the above, the blasting parameters of a multi-joint underground rock mass in an alpine region were optimized: hole spacing 4.0 m, row spacing 2.5 m, hole depth 11.5 m, V-type initiation network. The optimized blasting parameters significantly improved the mining efficiency and reduced the large lump rate to 3.1%. In order to promote the sustainable exploitation of resources in alpine regions, this study optimized the blasting technology of underground rock mass

Laboratory-Based Investigation into Stress Corrosion Cracking of Cable Bolts

Cable-bolt failures due to stress corrosion cracking (SCC) could significantly compromise the sustainability and long-term stability of underground constructions. To fully understand the SCC of cable bolts, a two-step methodology was implemented: (i) long-term cable-bolt coupon tests using mineralogical materials collected from underground mines; and (ii) accelerated full-scale cable-bolt tests using an acidified solution. In the long-term tests, a novel three-point bending coupon was designed. The effects of mineralogical materials on SCC were evaluated under the simulated underground bolting conditions through the application of “corrosion cells”. For accelerated tests, SCC resistance of different type of cable bolts was examined using the new designed tensile-loading apparatus under the periodically increasing strain-rate loading mechanism. It was identified that mineralogical materials and applied stress intensity accelerated the corrosion process of the cable bolts. The number of wires and wire surface conditions in different types of cable bolt directly affected SCC susceptibility. The cable bolts with a greater number of wires provided higher resistance to SCC. The developed experimental methodologies can be applied to study SCC in other reinforcement materials and the results can be used to design optimal support systems in different environmental and geotechnical conditions

Study on Blasting Effect Optimization to Promote Sustainable Mining under Frozen Conditions

In order to respond to the theme of national green and healthy sustainable development and in response to the problems of large block rates and pollution of the environment after the blast mining of underground rocks in alpine areas, we conducted research on the joints of underground rocks and the blastability of frozen rocks. According to the actual geological conditions of an underground mine blasting in Heilongjiang Province, three kinds of joint blasting geometric models were established. The rock mass blasting process of different types of joints was simulated by LS-DYNA software and the influence law of joints on rock mass blasting was summarized. The blasting crater test and the triaxial compression test of frozen rock were carried out. Combined with the blasting fragmentation characterization function (R-R and G-G-S), the blasting fragmentation, strength and stiffness of frozen rock at different temperatures were obtained. Based on the above, the blasting parameters of a multi-joint underground rock mass in an alpine region were optimized: hole spacing 4.0 m, row spacing 2.5 m, hole depth 11.5 m, V-type initiation network. The optimized blasting parameters significantly improved the mining efficiency and reduced the large lump rate to 3.1%. In order to promote the sustainable exploitation of resources in alpine regions, this study optimized the blasting technology of underground rock mass