Obstacle avoidance handling and mixed integer predictive control for space robots

This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks. Firstly, a novel kind of obstacle avoidance constraint of space robots, which needs the assumption that the manipulator links and the obstacles can be represented by convex bodies, is proposed by limiting the relative velocity between two closest points which are on the manipulator and the obstacle, respectively. Furthermore, the logical variables are introduced into the obstacle avoidance constraint, which have realized the constraint form is automatically changed to satisfy different obstacle avoidance requirements in different distance intervals between the space robot and the obstacle. Afterwards, the obstacle avoidance constraint and other system physical limits, such as joint angle ranges, the amplitude boundaries of joint velocities and joint torques, are described as inequality constraints of a quadratic programming (QP) problem by using the model predictive control (MPC) method. To guarantee the feasibility of the obtained multi-constraint QP problem, the constraints are treated as soft constraints and assigned levels of priority based on the propositional logic theory, which can realize that the constraints with lower priorities are always firstly violated to recover the feasibility of the QP problem. Since the logical variables have been introduced, the optimization problem including obstacle avoidance and system physical limits as prioritized inequality constraints is termed as MIPC method of space robots, and its computational complexity as well as possible strategies for reducing calculation amount are analyzed. Simulations of the space robot unfolding its manipulator and tracking the end-effector’s desired trajectories with the existence of obstacles and physical limits are presented to demonstrate the effectiveness of the proposed obstacle avoidance strategy and MIPC control method of space robots.     

主从式编队航天器连通性保持与碰撞规避

针对主从式航天器编队过程中存在的通信距离约束、航天器之间的碰撞以及空间干扰等问题，提出一种基于非线性干扰观测器和人工势函数的分布性协同控制方法。当初始通信网络连通时，通过在分布式协同控制器中引入吸引势函数，保证整个编队过程中通信网络始终是连通的。针对主航天器速度仅有部分从航天器直接可知的情况，为每一个从航天器设计分布式的速度观测器估计主航天器的速度，从而实现航天器之间的速度协同。此外，通过在控制器中引入非线性干扰观测器对外界干扰进行观测，显著增强了航天器编队的精度。仿真结果表明，本文提出的分布式协同控制方法不但能够实现对主航天器的速度跟踪以及航天器之间的队形保持，而且能够在编队过程中实现通信网络的连通性保持和航天器之间的碰撞规避。     

大面积三维场景中的无人机碰撞检测快速算法

无人机实时监控与驾驶员模拟训练系统的三维可视化子系统具有计算无人机与其他物体 (包括山脉、树木、建筑物等 )碰撞可能性、具体碰撞点、碰撞方向和碰撞力量的功能。但无人机测控系统中的三维场景可视面积很大 ,场景中的物体数量庞大 ,至使碰撞检测的运算量很大 ,因而会大幅度降低三维场景的实时性。因此 ,设计快速有效的碰撞检查算法十分必要。作者设计的快速算法快速有效 ,效果良好     

基于数字地图预处理的实时航迹规划

地形跟随／地形回避，威胁回避（TF／TA2）实时航迹规划是自主式TF／TA2低空突防系统的关键技术之一，本文在数字地图预处理技术的基础上，提出了完全曲面的概念，从而使三维最优航迹规划转化为在安全曲面上的二维规划，降低民规划维数，减少了存储量和计算量，提高了实时航迹规划的速度，使之更适于在机载条件下实现，文中同时提出了对未预知崦由机载传感器实测到的障碍和威胁的处理方法，使最优航迹能有效地回避这些障碍和威胁，仿真结果表明，文中所提出的实时航迹规划算法是有效的。     

能量最优的航天器连续动态避障轨迹规划

针对传统脉冲避障算法在航天器轨迹规划应用中存在对瞬时推力依赖性强且燃料消耗量大的问题,提出能量最优的连续动态避障算法。该算法首先基于线性相对运动方程与有限时间的能量最优模型,建立了相对运动能量最优模型,同时验证了模型最优性;其次将动态障碍物的 y 向运动误差偏移与正态分布概率引入避碰安全距离模型,修正了追踪航天器动态避障的范围,确定了安全距离矢量长度,增强了规避障碍的可靠性;最后通过障碍物速度矢量与追踪器航天器速度矢量夹角确定动态避障点方向,减少燃料消耗的同时提高了避障的有效性、准确性。通过仿真验证,该算法可以自适应选取规避障碍点,有效规避动态障碍;工质燃料消耗较小,有效延长航天器在轨寿命。     

一种基于单目视觉的自主机器人导航控制方法

首先对单目视觉获得的原始图像进行图像校正处理,利用边界判据函数分割获得可行区域,得到障碍物位置信息,然后在可行区域中根据障碍物位置分段给出机器人导航控制边界,最后采用拟合曲线模型得到前进路径曲线。试验表明,该算法有效稳定,可实时获取可行区域并实现移动机器人自主避障功能。     

半穿甲数值计算初步探讨：正碰撞均质钢甲计算

半穿甲子弹，又名穿甲爆破弹，其在侵彻一定厚度装甲后爆炸以起到杀伤破坏作用，因此子弹的侵彻机理和弹体的动强度问题就显得尤为重要。利用ANSYS／LS-DYNA3D计算软件对半穿甲子弹正碰撞均质钢甲的侵彻过程进行了数值模拟，并与试验结果进行了对比。     

Explicit expression of collision probability in terms of RSW and NTW components of relative position

The existing analytical and numerical computing methods for collision probability (P_c) provide sufficiently accurate results, but do not reveal the direct connection between P_c and conjunction geometry or error covariance. This paper derived an explicit expression of P_c under the circular orbit assumption, based on analysis of closest approach distance and Chan’s analytical formulae for P_c. The P_c was expressed as an explicit function of the radial, in-track, cross-track components of relative position and error covariance. The explicit expression is simple and compact, relates P_c with components of relative position, which are two kinds of important conjunction risk criteria. By introducing non-zero flight-path angle and ratio of velocity’s magnitude, a modified expression of P_c was presented for objects in eccentric orbits. For objects with eccentricity less than 0.01 (which account for 62% of all LEO objects), the relative error of the explicit expression is less than 0.107, or 0.252 for typical conjunction cases. What really matters in conjunction risk assessment is the order of magnitude rather than the specific value of P_c, the precision of the explicit expression is sufficient for conjunction risk assessment and decision-making for most LEO objects.     

天问一号着陆器双目视觉避障技术

对天问一号双目视觉避障技术的组成、方案及原理进行了介绍,通过图像障碍识别和双目立体地形感知完成天问一号降落过程中的安全着陆点自动选取.通过高分辨率双目匹配和亚像素插值处理,提高远距离双目测量精度;在计算资源严格受限的条件下,采用FPGA作为硬件加速平台,通过功能模块的并行化和流水线设计,提高计算视差和三维信息的速度;为...