This paper investigates the obstacle avoidance problem of autonomous vehicles in campus environment, and proposes a path planning algorithm based on OpenPlanner and hybrid A*. In the global planning stage, OpenPlanner’s global planner quickly plans a global path from the starting point to the destination using a vector map. In the local planning phase, OpenPlanner’s local planner samples and generates local trajectory clusters, while the hybrid A* dynamically adjusts the path based on the cost map to ensure the feasibility and safety of the path. In order to analyze the performance of the proposed planning scheme, an Autoware-based campus unmanned vehicle autopilot platform is built. The experimental results show that the unmanned vehicle successfully drives through turning intersections, complex road sections, and crossroads, and completes planning tasks such as obstacle avoidance, stopping, and cruising. Meanwhile, the success rate of obstacle avoidance is proved to be 96.67

This paper addresses key challenges in the 4SPS under-constrained parallel robot, focusing on geometric-static coupling modeling and control system design. A geometric-static coupling model is first established for the robot, which possesses six degrees of freedom. To solve this model, a Sine Cosine Dung Beetle Optimization (SCDBO) algorithm is developed, integrating refractive inverse learning, sine-cosine functions, and an adaptive t -distribution strategy to enhance global search capability and convergence accuracy. A terminal sliding mode controller incorporating a radial basis function (RBF) neural network with block approximation of the dynamic model (RBFNN-TSMC-BADM) is then proposed to handle system uncertainties and external disturbances, with its stability rigorously proved via the Lyapunov method. The effectiveness of the SCDBO algorithm in solving forward and inverse geometric-static problems and the trajectory tracking performance of the RBFNN-TSMC-BADM are validated through a case study of a temporary support robot in a coal mine.

The 4-PS parallel mechanism, with four kinematic chains, excels in heavy-load, large-stroke, and high-dynamic-response scenarios. However, when operating in complex dynamic environments with external disturbances and contact interactions, the 4-PS parallel mechanism exhibits significant degradation in pose tracking accuracy and contact force regulation. To address these challenges, this paper addresses two critical issues concerning the mechanism: contact dynamics and control under model uncertainties and external disturbances. First, a comprehensive dynamic model incorporating parametric model uncertainties and external disturbances is constructed for the 4-PS parallel mechanism, alongside its environmental contact model. Second, to compensate for model uncertainties and external disturbances, a fuzzy approximation system is employed to estimate sliding mode switching functions, augmented by an adaptive strategy to eliminate approximation residuals, thereby ensuring highly accurate pose tracking. Simultaneously, a fuzzy impedance controller is designed with force error and its rate as inputs to dynamically adjust damping and stiffness coefficients, achieving high-precision force tracking. Finally, simulations in a coal mine temporary support scenario demonstrate that the proposed adaptive fuzzy sliding mode impedance control strategy enables the mechanism to converge rapidly and accurately to the desired states, validating its effectiveness and reliability in simultaneous pose and force tracking for the 4-PS parallel mechanism.

The separation of coal and gangue plays a pivotal role in enhancing coal quality,reducing transportation costs,and mitigating environmental pollution,thereby facilitating the efficient and clean utilization of coal resources and promoting sustainable mine develop-ment.To address the challenges of high labor intensity and low efficiency inherent in traditional manual gangue sorting,a rigid-flexible hybrid-driven parallel gangue sorting robot consisting of a rigid drive rod and four cables is proposed.However,the dynamic impacts arising from the pick-and-place operation of the gangues,uncertainties in dynamic parameters,and external disturbances inevitably have an important influence on the tracking accuracy and stability of the gripper of the robot,potentially leading to the failure of the pick-and-place operation of the target gangues.As a result,the dynamics and robust model predictive control for the proposed rigid-flexible hybrid-driven parallel gangue sorting robot are investigated.First,a systematic scheme for the proposed rigid-flexible hybrid-driven parallel gangue sorting robot is presented,including an analysis of the degrees of freedom and the establishment of its kinematic model.Second,taking into account the parameter perturbations in the robot's model and external disturbances during the pick-and-place operation of the target gangues,the dynamic model of the robot is developed with the Newton-Euler method.Third,a robust model predictive control method incorporating tension constraints is proposed for the presented rigid-flexible hybrid-driven parallel gangue sorting robot,which op-timizes the real-time collaborative allocation of the driving forces of the four cables and the rigid drive rod.This method dynamically counteracts impacts and external disturbances during of the pick-and-place of the gangues,enabling high-precision trajectory tracking con-trol for the gripper of the robot.Finally,some simulations are performed for the proposed rigid-flexible hybrid-driven parallel gangue sort-ing robot using a spatial helical trajectory and a four-segment sorting trajectory.And the results demonstrate that the maximum trajectory deviation of the gripper is limited to 3.7×10-3 m,the attitude angle error stabilizes at 3.2×10-3 rad,and cable tensions consistently satisfy the driving force constraints.These findings verify the effectiveness of the proposed control strategy in reliable pick-and-place operation of the gangues under complex operational conditions.

Semantic segmentation is a crucial task in computer vision with broad applications in autonomous driving, intelligent surveillance, drone vision, and other fields. The current high-precision segmentation models generally suffer from large parameter sizes, high computational complexity, and substantial memory consumption, which limits their efficient deployment in embedded systems and resource-constrained environments. In addition, traditional methods exhibit significant limitations in handling multi-scale targets and object boundaries, particularly during deep feature extraction, where the loss of shallow spatial information often results in blurred boundaries and reduced segmentation accuracy. To address these challenges, we propose EfficientSegNet, a lightweight and efficient semantic segmentation network. This network features an innovative architecture that integrates the Cascade-Attention Dense Field (CADF) module and the Dynamic Weighting Feature Fusion (DWF) module, effectively reducing computational resource requirements while balancing global semantic information and local detail recovery. Experimental results demonstrate that EfficientSegNet achieves an excellent balance between segmentation accuracy and computational efficiency on multiple public datasets, providing robust support for real-time segmentation tasks and applications on resource-constrained devices.

Equipped with one degree of freedom in one-dimensional translation of the base, a mobile dual-arm robot (MDAR) is proposed in this paper, and the two arms and the base move simultaneously. As a result, the motion of the base has a significant influence on the motion of both end-effectors at the same time, and the relative positions of the two end-effectors change all the time. Therefore, this paper focuses on the main issues related to the presented MDAR in two key areas: the relative dynamics and relative force/position hybrid control. First, based on the D-H parametric method, the relative kinematics of the proposed MDAR is established, and the relative Jacobian matrix of the robot is derived. Secondly, the dynamic model of the proposed MDAR is constructed using the Lagrangian method. Furthermore, a closed-loop control strategy for relative force/position hybrid control of the MDAR based on the relative dynamics is proposed to enable the two end-effectors of the MDAR to track the planned trajectory accurately. Finally, a simulation is carried out on a dual-arm cutting robot (DACR) for a coal mine to prove the effectiveness of the proposed relative dynamics and the proposed relative force/position hybrid control law in terms of the absolute error (AE) and root mean square error (RMSE). The results show that the proposed relative dynamic model and relative force/position hybrid control can significantly reduce error of the DACR, effectively improve the adaptability and operation accuracy of the system to complex environment, and verify the feasibility and superiority of the method in practical application.

To address the challenges in synthetic aperture radar (SAR) ship detection, including complex target backgrounds, multiscale ships, and diverse orientations, while also meeting the lightweight requirements for satellite-based applications, we propose a lightweight multiscale feature fusion network—MSCF-Net. First, we design a lightweight dilation-wise residual C2f (DRC2F) module that enhances the network’s multiscale feature extraction capability through a two-stage residual mechanism and multiscale depth-wise separable dilated convolutions. Second, to overcome the limitations of traditional feature fusion methods in SAR ship detection, we propose a multiscale channel feature fusion pyramid network, MSCF-FPN, which effectively suppresses background noise interference while highlighting foreground target features through multimodal pooling and dynamic feature calibration mechanisms. Finally, to further improve detection accuracy on SAR images characterized by low target-background discriminability and diverse target orientations, we propose a multibranch decoupled detection head integrated with receptive-field attention to improve the detection head’s capacity to perceive spatial as well as orientation information. Experimental results demonstrate that MSCF-Net achieves detection accuracies of 79.1% (+4.9%) and 92.1% (+2%) on the SRSDD-v1.0 and high-resolution SAR images dataset (HRSID), respectively, with mean average precisions of 71.7% (+5.8%) and 93.3% (+0.2%). Furthermore, the number of model parameters is decreased from 10.89M to 4.66M, a reduction of approximately 57.2%, striking an effective balance between detection performance and model efficiency. In addition, MSCF-Net exhibits robust generalization capabilities on large-scene SAR images, rendering it well-suited for application in complicated real-world scenarios.

This paper focuses on six-degree-of-freedom (six-DOF) spatial cable-suspended parallel robots with eight cables (8-6 CSPRs) because the redundantly actuated CSPRs are relevant in many applications, such as large-scale assembly and handling tasks, and pick-and-place operations. One of the main concerns for the 8-6 CSPRs is the stability because employing cables with strong flexibility and unidirectional restraint operates the end-effector of the robot under external disturbances. As a consequence, this paper attempts to address two key issues related to the 8-6 CSPRs: the force-pose stability measure method and the stability sensitivity analysis method. First, a force-pose stability measure model taking into account the poses of the end-effector and the cable tensions of the 8-6 CSPR is presented, in which two cable tension influencing factors and two position influencing factors are developed, while an attitude influence function representing the influence of the attitudes of the end-effector on the stability of the robot is constructed. And furthermore, a new type of workspace related to the force-pose stability of the 8-6 CSPRs is defined and generated in this paper. Second, a force-pose stability sensitivity analysis method for the 8-6 CSPRs is developed with the gray relational analysis method, where the relationship between the force-pose stability of the robot and the 14 influencing factors (the end-effector's poses and cable tensions) is investigated to reveal the sequence of the 14 influencing factors on the force-pose stability of the robot. Finally, the proposed force-pose stability measure method and stability sensitivity analysis method for the 8-6 CSPRs are verified through simulations.

The China Siwei SVN2-03 and SVN2-04 satellites are equipped with interferometric synthetic aperture radar (InSAR) systems, which provide an excellent source of data for acquiring high-precision raw digital surface models (RawDSM). However, its unique operational mode also imposes specific technical requirements on data processing methods. This paper details the interferometric processing methods and RawDSM generation techniques that have been tailored to SVN2 satellites, taking into account their operational characteristics. Key steps, such as data registration, is optimised during the interferometric processing stage. A comprehensive technical workflow has been established for generating RawDSM, covering everything from phase information extraction to elevation inversion. To validate the proposed techniques, experiments are conducted to generate RawDSM using actual observation data from the SVN2 satellites. The results of these experiments conclusively demonstrate that the RawDSM generation technique described herein is highly adaptable to SVN2 satellites data. This technique enables the efficient generation of high-precision RawDSM, providing technical support for the subsequent production of DSM products and three-dimensional geospatial information applications.

Facing the support challenges of short-wall working face (15–40m) roadways in the ‘excavation–backfill–retention’ tunneling method for section coal pillars, traditional equipment struggled to achieve stable, reliable, and efficient support. This paper designed a temporary support robot for the excavation and mining system of section coal pillars to ensure the safety of equipment and personnel in short-wall working faces. The support requirements of the section coal pillar excavation and mining system were analyzed, and a general ‘driving under pressure’ temporary support scheme was proposed. The working principle of the temporary support robot was analyzed. A mechanical model for the stable support of the temporary support robot was established. The mechanical properties of the surrounding rock were analyzed, and the allowable range of the temporary support robot’s supporting force was determined while ensuring the stability of the surrounding rock. Based on the Stribeck friction theory, a dynamic model of the temporary support robot in the driving under pressure state was constructed. The boundary conditions of the dynamic model were set, and the corresponding relationship between the temporary support robot’s supporting force and its maximum static friction force was determined. This accurately described the influence of the supporting force and pushing (pulling) force on the movement during the process of driving under pressure. Through finite element simulation, the stress conditions of the temporary support robot and the floor under maximum load were analyzed, indicating that this load condition would not cause damage to the temporary support robot or the surrounding rock. Through multi-body dynamics simulation, the pushing (pulling) forces required for the temporary support robot’s movement under different supporting force conditions were obtained, verifying the feasibility of the driving under pressure action under different supporting force conditions. Moreover, the model-predicted and simulated values of the required pushing (pulling) forces during the process of driving under pressure were consistent, validating the accuracy of the driving under pressure dynamic model. This research provides a new theoretical framework for the design and dynamic analysis of temporary support equipment for short-wall working faces in section coal pillar mining, holding significant academic value and broad application prospects.

The shield type intelligent tunneling robot system effectively solves the problem of"mining excavation imbalance,fast mining,and slow tunneling"in coal mining,as an important component of the system,temporary support robots play a crucial role in improving operational efficiency.However,due to structural limitations,the temporary support robots can only achieve vertical lifting movements,making it difficult to effectively cope with the temporary support operations of complex roadways.To solve the problem of limited motion of the temporary support robot,an under-constrained temporary support robot was designed,and a terminal sliding mode control method based on RBF neural network block approximation was proposed to achieve high-precision motion control of the under-constrained tem-porary support robot.Firstly,the modified G-K formula was used to analyze the degrees of freedom of the robot.In response to the diffi-culty in solving the forward kinematics of the under-constrained temporary support robot,a geometric static coupling model was estab-lished,and an improved dung beetle optimization algorithm was proposed to solve the forward and inverse geometric static problems,and simulations of the geometric static problems were carried out.Secondly,a terminal sliding mode controller based on RBF neural network block approximation was designed.Given the uncertainty of the parameter matrix of the end support platform,multiple sets of RBF neural networks were used to approximate it,and the weights were adjusted online according to the adaptive law to realize the reconstruction of the dynamic model,and a robust term was designed to eliminate the model reconstruction error and external disturbances.To alleviate the chattering problem of the controller,a fuzzy system was designed to adaptively approximate the switching gain to replace the robust term,and the stability of the control system was proved by using the Lyapunov criterion.Finally,a simulation was carried out with a planar cir-cular trajectory as an example.The results show that the single-point verification accuracy of the improved dung beetle optimization al-gorithm for forward and inverse kinematics is less than 10-20,and the continuous kinematics solution results are good.The position track-ing error of the terminal sliding mode control method using RBF neural network block approximation for the predetermined trajectory is 0-0.011 m,and the attitude tracking error is 0-0.003 1°.Compared with the overall approximation of the RBF neural network and PD con-trol,the maximum tracking error is reduced by 99.0%and 95.5%respectively,and the root mean square error is reduced by 98.3%and 96.5%respectively.It is proved that the terminal sliding mode control method based on RBF neural network block approximation can fur-ther improve the motion control accuracy of the under-constrained temporary support robot and has stronger robustness under the condi-tion of external interference.

Cable-driven parallel robots (CDPRs) have attracted much attention due to a lot of advantages over conventional parallel robots. One of the main issues is the stability of the robot, which employs cables with strong flexibility and unidirectional restraint to operate the end-effector leads. As a result, this presented article aims to propose a systematic approach to the stability measures for the CDPRs by means of combining the cable tensions and poses of the end-effector. First, two position-influencing factors having important effects on the stability of the CDPRs are presented based on their kinematic model. Then, two cable tension-influencing factors also having essential effects on the stability of the robot are developed based on the determinations of cable tensions. Meanwhile, a function representing the effects of the end-effector's attitudes on the stability of the robots is constructed. Furthermore, the stability measures for the CDPRs are addressed, where a systematic stability measure approach is presented and three stability measure applications, average stability, minimum stability, and weighted average stability, are presented. Subsequently, a specified stability workspace is designed with the proposed force-pose stability measure approach. Finally, the approach to the force-pose stability measures and specified stability workspace generation algorithm are explained through simulation results of a spatial cable-driven parallel robot with 6-DOF with eight cables.

Recently, the maximum correntropy criterion in information theoretic learning has been employed in the design of Kalman filters, which performs well under non-Gaussian noises problem. How to extend the maximum correntropy Kalman filter to the distributed framework has become a significant focus of many researchers. This paper utilizes consensus protocol to implement distributed fusion in sensor networks and Hankel matrices to improve the estimation performance of distributed Kalman filter. The consensus iteration values obtained by the consensus algorithm are stored in the sensor nodes, and the Hankel matrices are constructed from the differences of these iteration values. By calculating the normalized kernels of these Hankel matrices to obtain the final consistent estimates, a finite-time consensus distributed maximum correntropy Kalman filter is proposed. The proposed algorithm is able to reduce the number of consensus iterations and achieve accurate average consensus under non-Gaussian noises. Based on the stochastic stability lemma, we prove the stability of the proposed filter. Finally, numerical simulation examples are given to verify the effectiveness of the proposed algorithm.

Due to the difficulty of accurately predicting system reliability for many engineering structures, bounds on system reliability have received increasing attention. By dealing with structural uncertain parameters with an ellipsoid model, a linear programming-based non-probabilistic reliability bounds method is proposed in this paper for series systems. In this research, a linear programming model is first established, and then several strategies are proposed to simplify the model by removing zero design variables. Three numerical examples are presented to demonstrate the feasibility and validity of the proposed method.

There is an unbalanced problem in the traditional laneway excavation process for coal mining because the laneway excavation and support are at the same position in space but they are separated in time, consequently leading to problems of low efficiency in laneway excavation. To overcome these problems, an advanced dual-arm tunneling robotic system for a coal mine is developed that can achieve the synchronous operation of excavation and the permanent support of laneways to efficiently complete excavation tasks for large-sized cross-section laneways. A dual-arm cutting robot (DACR) has an important influence on the forming quality and excavation efficiency of large-sized cross-section laneways. As a result, the relative kinematics, workspace, and control of dual-arm cutting robots are investigated in this research. First, a relative kinematic model of the DACR is established, and a closed-loop control strategy for the robot is proposed based on the relative kinematics. Second, an associated workspace (AW) for the DACR is presented and generated, which can provide a reference for the cutting trajectory planning of a DACR. Finally, the relative kinematics, closed-loop kinematic controller, and associated workspace generation algorithm are verified through simulation results.

According to the process and characteristics of the gangue sorting,a grasping trajectory planning scheme for the cable-driven gangue sorting robot was proposed.The kinematic model of the cable-driven gangue sorting robot was firstly expounded,and the accuracy of the model was verified by simulation,which provided a basis forjudging whether the trajectory of the end grab conforms to the change rule of the cable length.According to the characteristics of synchronous movement of the gangues and belt conveyor,the position of the gangue bin and the workspace geometric center,the grasping trajectory of the end grab was then planned four sections,namely as start,preparation,gangue grab,and gangue disposal sections.According to the different motion characteristics of the above sections,the S-type velocity curve,quintic polynomial and the combination of both were used to plan the motion of the end grab.The planned trajectory scheme was finally simulated and analyzed.The results showed that the trajectory,velocity and acceleration of the end grab were continuous,the change of cable length was smooth and continuous,and the trajectory parameters determined by the above method could adapt to the different distribution of gangue on the belt conveyor.

Employing cables with strong flexibility and unidirectional restraints to operate a camera platform leads to stability issues for a camera robot with long-span cables considering the cable mass. Cable tensions, which are the constraints for the camera platform, have a critical influence on the stability of the robot. Consequently, this paper focuses on two special problems of minimum cable tension distributions (MCTDs) within the workspace and the cable tension sensitivity analysis (CTSA) for a camera robot by taking the cable mass into account, which can be used to investigate the stability of the robot. Firstly, three minimum cable tension distribution indices (MCTDIs) were proposed for the camera robot. An important matter is that the three proposed MCTDIs, which represent the weakest constraints for the camera platform, can be employed for investigating the stability of the robot. In addition, a specified minimum cable tension workspace (SMCTW) is introduced, where the minimum cable tension when the camera platform is located at arbitrary position meets the given requirement. Secondly, the CTSA model and cable tension sensitivity analysis index (CTSAI) for the camera robot were proposed with grey relational analysis method, in which the influence mechanism and influence degree of the positions of the camera platform relative to cable tensions was investigated in detail. Lastly, the reasonableness of the presented MCTDIs and the method for the CTSA with applications in the stability analysis of the camera robot were supported by performing some simulation studies.

Owing to the existing problems of the temporary shield support device in a coal mine, such as considerable component weight, difficult disassembly, and large chamber installation, the design of the temporary rectangular shield support device was optimized. A module division method combining the functional analysis method and a similar feature clustering method was proposed, which completes the division of the functional module and establishes the structural module. A structural optimization method of “variable density topology optimization, parameter sensitivity analysis and Optimal Space-Filling Design (OSF)” was proposed. A variable-density topology optimization model of the device was established using the variable-density topology optimization method. The key variables of the device were determined using a parameter sensitivity analysis. The sample points of the critical variables were generated using the optimal space-filling design method, the approximate response surface models of mass, displacement, and stress were constructed, and the optimal solution of the device’s weight was obtained under the constraint conditions of pressure and displacement. A lightweight matching method of modularization based on transportability, disassembly, maintainability, and reliability was proposed, and the optimal matching scheme for the volume and mass of the device was determined. As a result, the weight of the temporary shield support device was reduced by 11.2%, and the maximum stress was reduced by 13.4%, under the premise of ensuring reliability. It realizes the convenience of transportation and high efficiency of assembly and disassembly in different design requirements, which is of great significance to accelerate the intelligent construction of coal mine.

Tracked inspection robots have demonstrated their versatility in a wide range of applications. However, challenges arising from issues such as skidding and slipping have posed obstacles to achieving precise and efficient trajectory control. This paper introduces a method to determine the steering parameters of robot based on the surrounding obstacles and road information. The primary objective is to enhance the steering efficiency of tracked robots. The corresponding relationship between the track speed, driving force and track steering radius of the tracked robot is obtained. Considering the influence of track skid and slip, relationship models about the steering radius and traveling speed of the robot are established. The minimum and maximum steering radii in the obstacle avoidance process are analyzed, and a mathematical model of the relationship between the steering angle of the robot and the distance between the side obstacles is established. The trajectory deviation model of the tracked robot is established, and a principle analysis of the LiDAR ranging is completed. This lays the foundation for a steering measurement and control system for tracked robots. ADAMS(2020) software is used to establish the multi-body dynamics model of the tracked robot, and three different obstacle-avoiding steering control strategies are designed for the robot in a simulated environment with space obstacles. The simulation experiment demonstrates that the robot achieves more efficient obstacle avoidance steering through the use of differential steering, leading to a decrease in both track skid and slip rates. Through the simulation experiment, it can be seen that the robot uses differential steering to complete the obstacle avoidance steering movement more efficiently, and the track skid and slip rates are smaller. The simulation results are used to complete the steering control experiment of the tracked robot on different road surfaces. The results show that by adjusting the track driving parameters, the robot can effectively complete the obstacle-avoiding steering movement by using the differential steering control strategy, which verifies the accuracy of the steering control strategy.

The separation of gangues from coals with robots is an effective and practicable means. Therefore, a cable-suspended gangue-sorting robot (CSGSR) with an end-grab was developed in our early work. Due to the unidirectional characteristic, the flexibility of cables, and the dynamic impact of pick-and-place gangues, one of the significant issues with the robots is robustness under internal and external disturbances. Cable tensions, being the end-grab's constraints, have a crucial effect on the robustness of the CSGSR while disturbances are on. Two main issues related to the CSGSR, as a result, are addressed in the present paper: minimum dynamic cable tension workspace generation and a sensitivity analysis method for the dynamic cable tensions. Firstly, the four cable tensions and minimum dynamic cable tension while the end-grab was located at an arbitrary position of the task space were obtained with the dynamics of the CSGSR. In addition, with the dynamics of the CSGSR, a minimum dynamic cable tension workspace (MDCTW) generating approach is presented, where the minimum dynamic cable tensions are greater than a preset value, therefore ensuring the robustness of the end-grab under the disturbances. Secondly, a method for dynamic cable tension sensitivity (DCTS) of the robots is proposed with grey relational analysis, by which the influence degree of the end-grab's positions on the four dynamic cable tensions and the minimum dynamic cable tensions was considered. Finally, the effectiveness of the proposed MDCTW generation algorithm and the DCTS analysis method were examined through simulation on the CSGSR, and it was indicated that the proposed MDCTW generation algorithm and the DCTS analysis method were able to provide theoretical guidance for pick-and-place trajectory planning and generation of the end-grab in practice.