地下矿用车辆无人驾驶目标路径规划方法研究

针对井下巷道复杂多变的路面条件,将地下矿用车辆无人驾驶目标路径划分为主目标路径和局部避障目标路径,在主目标路径规划时不必考虑局部避障问题,在主目标路径规划完成后,再进行局部避障目标路径规划。建立车辆轨迹跟踪偏差控制模型及动力转向控制模型,通过对模型的仿真计算,可对地下矿用车辆无人驾驶目标路径进行规划及优化。该目标路径规划方法具有简单方便和灵活可靠的优点。     

小型无人机气动肌腱式弹射系统动态仿真与优化

针对冲击气缸式无人机弹射系统耗气量高、质量大、动态特性差等弊端，提出了一种仿生气动肌腱式无人机弹射系统，利用气动肌腱的弱非线性，通过配置楔角以改善无人机加速阶段的受力情况，减缓加速度波动。对该弹射系统进行数学建模和动力学分析，并搭建Simulink模型对该系统进行仿真求解；通过MATLAB与Simulink对现有加速轨道通过多目标遗传算法实现进一步优化。优化后的加速轨道能提升加速度均值、气动肌腱能量利用率和起飞速度，且降低了加速度峰值，加速度波动在原有基础上降低了76.79%。仿真和优化结果表明，提出的气动肌腱式无人机弹射系统不仅避免了冲击气缸式弹射系统的缺点，还能进一步平缓加速度，减小整体系统的最大过载。     

Distributed allocation and dynamic reassignment of channels in UAV networks for wireless coverage

Providing wireless coverage to users using Unmanned Aerial Vehicles (UAVs) encounters two major challenges: deployment and channel allocation. To this end, solutions to both issues are proposed in this paper. An overloaded UAV attempts to acquire more channels by performing channel bonding/aggregation followed by requesting its chosen peers to move closer for load sharing. The proposed channel reallocation schemes minimize interference caused by channel reassignments, or change in network topology. The simulation results show that when employing these schemes, more data is served with reduced discontinuous service time and efficient usage of limited battery power.     

基于stackelberg多步博弈的无人机协同搜索路径规划

考虑到现有无人机搜索问题研究中无人机、移动目标仅有一方具有远距离探测能力的设定，已经无法体现出战场环境下双方的博弈关系。针对这一不足，基于stackelberg均衡策略，结合多步预测的思想，提出了stackelberg多步博弈策略，实现了无人机、目标都具有远距离探测能力的博弈搜索。通过建立无人机、目标各自的路径收益函数，使双方能够根据不同时刻的博弈状态选择相对应的函数，实现无人机的动态路径规划。仿真结果表明所提出策略完全适用于该博弈模型，比贪婪策略具有更高的搜索效率，大大提高了目标捕获率。     

Flight control of a hexa-rotor airship: Uncertainty quantification for a range of temperature and pressure conditions

The present paper is concerned with the dynamic modeling and design of control laws for a small non-rigid multi-rotor airship constituted of an oblate-spheroid helium balloon coupled with an electric-powered hexa-rotor airframe. The vehicle is assumed to operate in windless and low-speed conditions. A six-degree-of-freedom nonlinear dynamic model is derived for it using the Newton–Euler approach and considering, among other efforts, a restoring torque due to the displacement of the balloon’s center of buoyancy above the vehicle’s center of mass and the added-mass effect resulting from the air–structure interaction. Using the derived model and assuming a time-scale separation between the translational and rotational dynamics, the attitude and position control laws are designed separately from each other. Both laws are formulated using feedback linearization combined with control input saturation within appropriate parallelepipedal sets, which are carefully chosen to respect pre-defined bounds on the control torque, control force and maximum inclination angle. The effect of temperature and pressure fluctuations is taken into account through a parametric probabilistic approach, where Maximum Entropy Principle is used to construct a physically consistent stochastic model and Monte Carlo method is used as the stochastic solver to propagate the uncertainties through the system. Extensive simulation results show the effectiveness of the proposed control system and quantify the uncertainty of its performance over a wide range of local temperature and pressure.     

矿用无人卡车国内外研究现状及关键技术

分析了国内外露天矿山用卡车无人驾驶技术发展现状,详细介绍了露天矿山卡车无人驾驶关键技术;通过分析对比前装线控和后装线控两种技术路线的优缺点以及超声波雷达、毫米波雷达、激光雷达、4D光场智能感知系统、红外传感器、视觉传感器等环境感知技术的优缺点;提出多传感器高度融合将是露天矿山卡车实现全天候环境感知的发展方向。通过分析对比惯性导航系统、GNSS差分定位技术、车联网定位技术、电子地图定位技术、视觉传感器等定位导航技术的差异,指出多定位技术融合是露天矿山无人驾驶卡车定位方式的必然选择。结合露天煤矿的生产实际,提出将现有的无人驾驶各种技术算法与露天矿山标准作业流程有机融合是实现卡车无人驾驶的必由之路。最后指出无人驾驶卡车应用5G技术是露天矿山安全生产的关键和核心,是无人驾驶的必备技术。     

荔浦市岩质崩塌形成条件及失稳运动特征

通过对荔浦市境内碳酸盐岩区岩质崩塌及该区域地质环境条件的调查,总结了岩质崩塌的规模、发育高度、控制结构面等发育特征,分析了岩质崩塌形成条件,并判断岩质崩塌的失稳运动特征。本文以一处危岩为例,用无人机进行三维扫描并分析其形成原因及预测其失稳运动特征。     

同频段混合信号中的无人机信号盲检测识别

无人机信号的探测识别技术是应对无人机黑飞滥用的关键技术之一。在实际信号监测环境中，经常会接收到多个信号的混合信号，它们在时域和频域上混叠且各信号分量调制样式相同。为解决在同频段混合信号中检测识别出无人机信号的问题，提出了一种通过谱特征分析判断无人机信号存在性的方法。分别采用基于二次方谱特征的无人机图传和WiFi混合信号检测识别算法以及基于频谱带宽特征的多无人机混合信号检测识别算法，通过对射频电路采集的信号进行仿真验证，实现了从同频段混合信号中检测识别出无人机信号分量。理论分析和实验测试结果证实了所提检测识别算法的有效性。     

Cooperative path planning with priority target assignment and collision avoidance guidance for rescue unmanned surface vehicles in a complex ocean environment

In this paper, a novel cooperative path planning scheme of unmanned surface vehicles (USVs) for rescuing targets in a complex ocean environment is proposed. The primary objective of the rescue USVs is to bring all targets back safely on the premise of first rescuing priority targets, while optimizing the path length, the navigation time and the angular energy. The main contributions of this paper are as follows: (1) The proposed K-means-division (KMD) algorithm is able to identify a complex ocean environment with collision-free zone and static-obstacles zone; (2) The proposed path planning method with fast-marching-method-based ellipse guidance range (E-FMM) is able to optimize the angular energy while ensuring safety; (3) The proposed cooperative management system (including priority-target-assignment (PTA) with reward-mechanism genetic-optimization (RM-GO) and collision-avoidance (CA) guidance law with Tangent-based surge-varying wave-disturbances-observer (Tangent-SV-WDO)) can accomplish the mission of the rescue USVs. Comparative studies with the state-of-the-art methods demonstrate that the proposed cooperative path planning scheme is superior in terms of priority-target-assignment (PTA) and collision-avoidance (CA) of the actual rescue work.