Solar sailing in realistic mode,based on a locally-optimal control laws

Ballistic design of solar sailing missions in the solar system is composed of defining the design parameters, the control programs, and the trajectories that provide performance goals of a flight. The use of a solar sail spacecraft imposes specific restrictions on mission parameters that include the degradation limit on the flight duration, the maximum temperature of solar sail's surface, the minimum distance from the Sun, the maximum angular velocity of the spacecraft's rotation and others.Many authors considered the impact of these restrictions on the design of the mission separately, but they used a sophisticated method of finding the exact optimal motion control or applied the most straightforward laws of motion control. This paper uses local-optimal control laws at the complete mathematical models of motion and functioning of solar sail spacecraft to describe a technique of designing interplanetary missions. The described method avoids the need to obtain an accurate optimal solution to the control problem and does not cause significant computational difficulties.     

Pose measurement and motion estimation of non-cooperative satellite based on spatial circle feature

Malfunctioned satellites have seriously threatened orbital safety, and the capture of these satellites is of great significance. The pose measurement and the motion estimation of the tumbling satellite is the premise of capture. In this paper, the docking ring of the satellite is identified, which is equivalent to a spatial circle. Combined with the nozzle feature, the pose duality of the spatial circle can be eliminated. And the measurement accuracy is improved by minimizing the reprojection error of the docking ring and the nozzle. Due to the symmetry of the docking ring, the measured pose has only five degrees of freedom, losing the degree of freedom of rotation around the normal vector. In the motion estimation algorithm, the observability of the tumbling motion is firstly analyzed, then an error-state Kalman filter with inertia ratio constraints is designed. To improve the convergence speed and stability of the filter, a rough estimation algorithm of filter initial value based on linear term extraction and particle swarm optimization is proposed. The effectiveness of the pose measurement and motion estimation method is verified by simulations.     

柔性机械臂辅助空间站舱段对接阻抗控制

空间机械臂辅助舱段对接过程中存在测量与控制误差,易导致对接机构间存在较大接触力,传统FMA (Force MomentAccommodation)控制方法在测量接触力时无法消除大负载惯性力对测量的影响,且测量仪器的引入会进一步降低空间柔性机械臂的刚度。为此,文章提出了柔性机械臂辅助大负载空间舱段对接的阻抗控制方法,采用拉格朗日法推导了空间机械臂的关节输入力矩方程作为前馈输入,建立了含动力学前馈的空间机械臂阻抗控制程序,并以在商业软件ADAMS中建立的空间柔性机械臂与对接舱段组成的系统动力学模型作为控制对象,对系统进行ADAMS灢Matlab联合仿真。仿真结果表明,按照此控制方法,系统可克服外力干扰使目标解析点按照期望的方式运动;同时,通过测量机械臂关节运动参数即可实现对外力的准确感知,而不需额外添加力传感器,既消除了大负载惯性力对测量的影响,也不会导致柔性机械臂刚度的降低。     

机载SAR径向运动补偿的研究

运动补偿是实现高分辨率机载 SAR成像的关键问题之一。文中根据载机实际轨迹相对于理想轨迹的偏差 ,详细推导由运动误差所引入的相位误差的表达式 ,给出对机载 SAR径向运动偏差进行补偿的实现方法及对定位精度的要求 ,并进行仿真验证 ,取得较好的补偿效果     

基于多模态感知与融合的无人车韧性导航系统

针对野外复杂环境下的无人车自主导航需要,建立了一种基于多源融合定位、语义建图与运动规划的智能导航系统.首先,针对IMU、轮式里程计、视觉SLAM与激光雷达SLAM等测量子系统,设计了误差状态扩展卡尔曼滤波器进行融合定位.其次,基于改进的CNN语义分割网络生成环境的语义图像,与3D激光雷达点云融合,并使用最大概率更新算法构建语义3D地图.接着,在语义和几何信息投影获得可通行性代价的基础上,提出了一种语义动态窗口的局部路径规划方法.最后,将以上感知、定位与规划方法整合成完整的智能导航系统,在城市与野外典型场景的测试中,相对定位误差小于0.4％D,具备一定的韧性导航定位和智能感知规划能力.     

Modeling and experimental validation of sawing based lander anchoring and sampling methods for asteroid exploration

This paper presents a novel lander anchoring system based on sawing method for asteroid exploration. The system is composed of three robotic arms, three cutting discs, and a control system. The discs mounted at the end of the arms are able to penetrate into the rock surface of asteroids. After the discs cut into the rock surface, the self-locking function of the arms provides forces to fix the lander on the surface. Modeling, trajectory planning, simulations, mechanism design, and prototype fabrication of the anchoring system are discussed, respectively. The performances of the system are tested on different kinds of rocks, at different sawing angles, locations, and speeds. Results show that the system can cut 15?mm deep into granite rock in 180?s at sawing angle of 60°, with the average power of 58.41?W, and the “weight on bit” (WOB) of 8.637?N. The 7.8?kg anchoring system is capable of providing omni-directional anchoring forces, at least 225?N normal and 157?N tangent to the surface of the rock. The system has the advantages of low-weight, low energy consumption and balance forces, high anchoring efficiency and reliability, and could enable the lander to move and sample or assist astronauts and robots in walking and sampling on asteroids.     

Relevant experience learning: A deep reinforcement learning method for UAV autonomous motion planning in complex unknown environments

Unmanned Aerial Vehicles (UAVs) play a vital role in military warfare. In a variety of battlefield mission scenarios, UAVs are required to safely fly to designated locations without human intervention. Therefore, finding a suitable method to solve the UAV Autonomous Motion Planning (AMP) problem can improve the success rate of UAV missions to a certain extent. In recent years, many studies have used Deep Reinforcement Learning (DRL) methods to address the AMP problem and have achieved good results. From the perspective of sampling, this paper designs a sampling method with double-screening, combines it with the Deep Deterministic Policy Gradient (DDPG) algorithm, and proposes the Relevant Experience Learning-DDPG (REL-DDPG) algorithm. The REL-DDPG algorithm uses a Prioritized Experience Replay (PER) mechanism to break the correlation of continuous experiences in the experience pool, finds the experiences most similar to the current state to learn according to the theory in human education, and expands the influence of the learning process on action selection at the current state. All experiments are applied in a complex unknown simulation environment constructed based on the parameters of a real UAV. The training experiments show that REL-DDPG improves the convergence speed and the convergence result compared to the state-of-the-art DDPG algorithm, while the testing experiments show the applicability of the algorithm and investigate the performance under different parameter conditions.     

Adaptive path planning for unmanned aerial vehicles based on bi-level programming and variable planning time interval

This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs’ relevant performances, with respect to sensory capability, maneuverability, and flight velocity limit. On the basis of a novel adaptability-involved problem statement, bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization. Additionally, both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability. A discrete-search-based path planning solution, embedded with four optimization strategies, is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces, within which different surface-to-air missiles (SAMs) are deployed. Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner, and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.     

跨介质航行器波浪环境入水流场演变和运动特性研究

跨介质航行器是一种既可以在空中飞行又可以在水下潜航的新概念航行器,基于仿生学原理,提出一种通过改变外形实现水空介质跨越的航行器模型,通过入水试验装置和计算流体动力学方法,对航行器带攻角从空气到水的介质跨越过程进行了试验和数值仿真研究,得到了跨介质入水过程航行器的运动姿态和入水空泡形态,并通过数值仿真得到了航行器的升力、阻力、速度和加速度演化规律。同时基于数值模拟方法对有波浪情况和静水情况下航行器入水过程空泡演变以及运动特性进行对比。结果表明:提出的航行器构型在水中具有较好的姿态调整能力,波浪的有无和波高的不同都会对航行体入水运动特性造成影响。     

柔韧性在训练中对提高学生运动成绩的影响

柔韧性在运动中具有重要意义,它是有效改进技术的必要基础,也是保证提高运动技术水平的基本因素之一。针对大学生在常规的业余训练中加大柔韧性的练习,能有效提高体能训练的质量,从而达到训练目的,提高运动成绩。