Analysis of reaction torque-based control of a redundant free-floating space robot

Owing to the dynamics coupling between a free-floating base and a manipulator,the non-stationary base of a space robot will face the issue of base disturbance due to a manipulator's motion.The reaction torque acted on the satellite base's centroid is an important index to measure the satellite base's disturbance.In this paper,a comprehensive analysis of the reaction torque is made,and a novel way to derive the analytical form of the reaction torque is proposed.In addition,the reaction torque null-space is derived,in which the manipulator's joint motion is dynamically decoupled from the motion of the satellite base,and its novel expression demonstrates the equivalence between the reaction torque null-space and the reaction null-space.Furthermore,the reaction torque acted as an optimization index can be utilized to achieve satellite base disturbance minimization in the generalized Jacobian-based end-effector Cartesian path tracking task.Besides,supposing that the redundant degrees of freedom are abundant to achieve reaction torque-based active control,the reaction torque can be used to realize satellite base attitude control,that is,base attitude adjustment or maintenance.Moreover,because reaction torque-based control is a second-order control scheme,joint torque minimization can be regarded as the optimization task in reaction torque-based active or in-active control.A real-time simulation system of a 7-DOF space robot under Linux/RTAI is developed to verify and test the feasibility and reliability of the proposed ideas.Our extensive empirical results demonstrate that the corresponding analysis about the reaction torque is correct and the proposed methods are feasible.     

空间机器人抓捕目标后的载荷分配

针对多臂空间机器人以软指接触形式抓捕目标后的情形,提出了一种综合考虑摩擦约束及机械臂能力约束的目标期望合外力的载荷分配方法。首先,建立空间机器人系统与目标的动力学方程,作为载荷分配问题的基础。然后,在地面机器人相关研究的基础上,建立机械臂末端与目标表面的软指接触模型,并建立二者之间的运动约束关系。为简化优化计算,将摩擦锥约束线性化,并建立考虑关节扭矩限制的机械臂能力约束,从而将抓捕力优化的非线性规划问题转化为线性规划问题。最后,采用双臂空间机器人模型进行数值仿真,表明所提方法针对目标各种形式运动进行载荷分配的有效性。     

空间细胞机器人接管控制的分布式控制分配

采用接管控制技术延长航天器寿命为在轨服务提供了一种新思路,本文提出一种利用空间细胞机器人实施航天器接管控制的方案。针对空间细胞机器人实施接管控制的控制分配问题,建立了空间细胞机器人实施接管控制的动力学模型。为实现分布式控制分配,提出了一种基于CBBA算法的接管控制分配算法,利用自由市场机制实现控制分配的分布和异步计算。综合考虑了执行能力匹配、剩余能量和执行器输出限制,定义了空间细胞机器人的收益函数,空间细胞机器人通过自由拍卖和一致性协商完成控制任务的分配。通过蒙特卡罗分析,将本文算法与集中式分配算法零空间修正伪逆法相比较并进行参数影响分析,本文算法在保证分配精度的情况下,具有能量均衡等能力。     

燃料电池无人机能源管理与飞行状态耦合

开展了燃料电池/锂电池（简称燃锂）混合动力无人机的能源管理与飞行状态耦合研究。综合顶层飞行任务规划与底层能源系统管理,以动力系统模型为耦合点联立能源系统与无人机运动方程,建立能源状态与运动状态耦合模型。针对燃锂混合最紧密的爬升过程,以迎角、转速和燃料电池的放电功率作为控制变量,建立了燃料消耗最小的能源管理与航迹规划耦合最优控制问题,研究不同爬升高度对最优控制过程的影响,并与模糊控制能源管理策略进行对比分析。针对大功率短时爬升和小功率长时巡航的典型任务特点,建立了燃锂最优混合问题。研究了最优的锂电池容量和燃料电池功率水平的混合量,以及爬升和巡航两阶段最优功率分配和飞行状态,分析了不同巡航目标高度对最优混合量和飞行状态的影响。结果表明：采用能源与航迹耦合的最优控制策略在给出最优功率流分配的同时,能够很好地兼顾飞行状态控制;对燃锂混合和飞行状态的综合优化可以有效地处理爬升和巡航阶段的能源需求矛盾,在给出最优燃锂混合量和飞行状态的同时,降低整个任务过程的燃料消耗。     

Detumbling strategy based on friction control of dual-arm space robot for capturing tumbling target

The rotational motion of a tumbling target brings great challenges to space robot on successfully capturing the tumbling target. Therefore, it is necessary to reduce the target’s rotation to a rate at which capture can be accomplished by the space robot. In this paper, a detumbling strategy based on friction control of dual-arm space robot for capturing tumbling target is proposed. This strategy can reduce the target’s rotational velocity while maintaining base attitude stability through the establishment of the rotation attenuation controller and base attitude adjustment controller. The rotation attenuation controller adopts the multi-space hybrid impedance control method to control the friction precisely. The base attitude adjustment controller applies the dual-arm extended Jacobian matrix to stabilize the base attitude. The main contributions of this paper are as follows: (1) The compliant control method is adopted to achieve a precise friction control, which can reduce the target angular velocity steadily; (2) The dual-arm extended Jacobian matrix is applied to stabilize the base attitude without affecting the target capture task; (3) The detumbling strategy of dual-arm space robot is designed considering base attitude stabilization, realizing coordinated planning of the base attitude and the arms. The strategy is verified by a dual-arm space robot with two 7-DOF (degrees of freedom) arms. Simulation results show that, target with a rotation velocity of 20 (°)/s can be effectively controlled to stop within 30 s, and the final deflection of the base attitude is less than 0.15° without affecting the target capture task, verifying the correctness and effectiveness of the strategy. Except to the tumbling target capture task, the control strategy can also be applied to other typical on-orbit operation tasks such as space debris removal and spacecraft maintenance.     

机器人系统的动态混合力/位置控制的几何原理

基于在位形空间中受约束系统的几何性质,对机器人系统的运动及所受的约束力进行研究。通过引入法空间及切空间的概念,实现了机器人运动及力的解耦控制,从而简化了控制系统。通过对双臂机器人系统的位置/力动态混合控制的数字仿真,说明本方法简单、可行。     

Inertial parameter estimation and control of non-cooperative target with unilateral contact constraint

In this paper, the relative sliding motion between the target and the manipulator’s end-effector is considered and characterized as a unilateral contact constraint. A new possible solution is presented to estimate the inertial parameters of a non-cooperative target while the relative sliding motion exists. First, the detailed analysis of the dynamical model is presented, and a parameter-explicit linear time-varying model is obtained. Then, an extended state observer is constructed based on the new model, which can effectively estimate the unknown inertial parameters of the target when relative sliding motion exists. As the modified reactionless controller requires the knowledge of inertial parameters, a hybrid post-capture control scheme is also established based on the switch law between different controllers. The correctness and efficiency of the proposed algorithm are validated by numerical simulation, which proves a potential framework for the non-cooperative target post-capture operation.     

Task planning for robotic manipulation in space applications

Space-based robotic systems will require novel technologies of planning and manipulation to accomplish complex tasks such as diagnosis, repair, and assembly task representation, discrete task planning, and control synthesis which provide a design environment for assembly systems, and which extend to planning of manipulation operations in unstructured environments. In this approach, assembly planning is carried out using the AND/OR graph representation which encompasses all possible partial orders of operations and may be used to plan assembly sequences. A novel algorithm for planning disassembly and repair using the AND/OR graph is introduced, and examples of repair sequences generated for a satellite electrical module are described. For discrete task planning, the configuration map facilitates search over discrete parameters in the space of bounded configuration sets     

自由翻滚故障卫星外包络抓捕及抓捕路径优化

自由翻滚故障卫星抓捕是航天器在轨服务及空间碎片清理的基础。由于难以确定固定抓捕点及目标运动参数不确定,传统机械臂抓捕方法无法适用类似自由翻滚故障卫星的空间非合作目标。提出一种具有鲁棒性的外包络抓捕方法及抓捕路径优化方案。外包络抓捕方式能够适用于自由翻滚故障卫星抓捕问题,其特点在于,第一,由抓捕末端执行器构成的抓捕包络可以包络空间目标,约束其运动并最终实现抓捕,因此不需要固定抓捕点;第二,末端执行器构成的抓捕包络,能够约束故障卫星运动,而两者之间的摩擦可以有效消除两者之间的相对运动最终成功抓捕翻滚目标。进一步,针对外包络抓捕方法,提出了一种最小燃料消耗及最小抓捕扰动的机械臂抓捕路径。为验证外包络抓捕方法的有效性,构建旋转立方星抓捕地面实验,并利用数值仿真验证外包络抓捕机械臂最优路径规划,仿真结果验证了所提出方法的有效性。     

基于多智能体混合学习的多星协同动态任务规划算法(英文)

针对多星协同动态任务规划问题,以往多采用基于启发式的重规划算法,但是由于启发式策略依赖于具体任务,使得优化性受到影响。注意到协同规划的历史信息对后续协同规划的影响,本文提出了一种基于策略迭代的多智能体强化学习和迁移学习的混合学习算法求解该问题近似最优策略。本文的多智能体强化学习方法利用神经网络描述各颗卫星的强化学习策略,通过协同进化的方法迭代搜索具有最优拓扑结构和连接权重的策略神经网络个体。针对随机出现的观测任务请求导致历史学习策略失效,通过迁移学习将历史学习策略转换为当前初始策略,保证规划质量前提下加快多星协同任务规划速度。仿真实验及分析结果表明本文算法对动态随机出现的任务请求有良好的适应性。     

基于混合规划策略的自由漂浮冗余机械臂减振运动规划(英文)

对自由漂浮柔性冗余机械臂系统的减振运动规划问题进行研究。首先,采用拉格朗日方法建立系统的动力学模型,并给出了减振运动规划的模型。其次,提出一种基于高斯伪谱法与直接打靶法的混合规划策略,用于求解运动规划问题。先利用高斯伪谱法将运动规划问题转化为一个非线性参数优化问题,并用遗传算法确定近似解,随后利用直接打靶法建立优化模型,将得到的近似解作为优化变量的初值,并采用序列二次规划算法求得精确解。最后,对算例进行分析,验证了基于混合规划策略得到的关节运动轨迹能够明显减小柔性臂杆的全局振动以及残余振动。数值计算的结果表明该方法对减振运动规划问题的求解是有效且稳定的。     

基于能量最优的敏捷遥感卫星在轨任务规划

针对敏捷遥感卫星对多个离散观测点在轨自主任务规划问题,在考虑姿态运动方程耦合性的基础上,将问题分解为空间资源调度问题和连续最优控制问题,进而提出了一种结合伪谱法和遗传算法的混合求解算法。该算法针对基于行商问题(TSP)模型建立的空间资源调度问题模型,选用二维编码结构对观测顺序和相对观测时间进行实数编码,并采用遗传算法求解观测序列和观测时间;针对判断观测时间可行性时涉及的时间最优控制问题、以及姿态转移过程中涉及的最小能量消耗问题,将其归结为连续最优控制问题,并基于Gauss伪谱协态变量映射定理,采用Gauss伪谱法进行求解。通过与基于单纯遗传算法的规划算法进行对比试验,本文所提出的基于伪谱法和遗传算法的混合求解策略针对目标问题,在典型工况下姿态转移过程中能量消耗降低60%。     

Workspace,stiffness analysis and design optimization of coupled active-passive multilink cable-driven space robots for on-orbit services

The use of space robots (SRs) for on-orbit services (OOSs) has been a hot research topic in recent years. However, the space unstructured environment (i.e.: confined spaces, multiple obstacles, and strong radiation interference) has greatly restricted the application of SRs. The coupled active-passive multilink cable-driven space robot (CAP-MCDSR) has the characteristics of slim body, flexible movement, and electromechanical separation, which is very suitable for extreme space environments. However, the dynamic and stiffness modeling of CAP-MCDSRs is challenging, due to the complex coupling among the active cables, passive cables, joints, and the end-effector. To deal with these problems, this paper proposes a workspace, stiffness analysis and design optimization method for such type of MCDSRs. Firstly, the multi-coupling kinematics relationships among the joint, cables and the end-effector are established. Based on hybrid series-parallel characteristics, the improved coupled active–passive (CAP) dynamic equation is derived. Then, the maximum workspace, the maximum stiffness, and the minimum cable tension are resolved, among them, the overall stiffness is the superposition of the stiffness produced by the active and the passive cable. Furthermore, the workspace, the stiffness, and the cable tension are analyzed by using the nonlinear optimization method (NOPM). Finally, an 8-DOF CAP-MCDSR experiment system is built to verify the proposed modeling and trajectory tracking methods. The proposed modeling and analysis results are very useful for practical space applications, such as designing a new CAP-MCDSR, or utilizing an existing CAP-MCDSR system.     

A modified forward and backward reaching inverse kinematics based incremental control for space manipulators

Forward and backward reaching inverse kinematics(FABRIK) is an efficient two-stage iterative solver for inverse kinematics of spherical-joint manipulator without the calculation of Jacobian matrix. Based on FABRIK, this paper presents an incremental control scheme for a free-floating space manipulator consists of revolute joints and rigid links with the consideration of joint constraints and dynamic coupling effect. Due to the characteristics of FABRIK, it can induce large angular movements on s...     

基于多智能体强化学习的空间机械臂轨迹规划

针对某型六自由度（DOF）空间漂浮机械臂对运动目标捕捉场景,开展了基于深度强化学习的在线轨迹规划方法研究。首先给出了机械臂DH （Denavit-Hartenberg）模型,考虑组合体力学耦合特性建立了多刚体运动学和动力学模型。然后提出了一种改进深度确定性策略梯度算法,以各关节为决策智能体建立了多智能体自学习系统。而后建立了"线下集中学习,线上分布执行"的空间机械臂对匀速直线运动目标捕捉训练系统,构建以目标相对距离和总操作时间为参数的奖励函数。最后通过数学仿真验证,实现了机械臂对各向匀速运动目标的快速捕捉,平均完成耗时5.4 s。与传统基于随机采样的规划算法对比,本文提出的自主决策运动规划方法求解速度和鲁棒性更优。     

Pre-impact trajectory planning for minimizing base attitude disturbance in space manipulator systems for a capture task

Aimed at capture task for a free-floating space manipulator, a scheme of pre-impact trajectory planning for minimizing base attitude disturbance caused by impact is proposed in this paper.Firstly, base attitude disturbance is established as a function of joint angles, collision direction and relative velocity between robotic hand and the target.Secondly, on the premise of keeping correct capture pose, a novel optimization factor in null space is designed to minimize base attitude disturbance and ensure that the joint angles do not exceed their limits simultaneously.After reaching the balance state, a desired configuration is achieved at the contact point.Thereafter, particle swarm optimization(PSO) algorithm is employed to solve the pre-impact trajectory planning from its initial configuration to the desired configuration to achieve the minimized base attitude disturbance caused by impact and the correct capture pose simultaneously.Finally, the proposed method is applied to a 7-dof free-floating space manipulator and the simulation results verify the effectiveness.     

模块化可重构卫星在轨自重构的分层规划

模块化可重构卫星具有组织灵活、操作方便、适应性强等特点，可以有效降低卫星研制和发射成本、提高卫星对紧急任务的响应速度、延长卫星寿命。重构规划问题对模块的具体移动方式进行求解，是实现自重构需要解决的核心问题之一。针对同构式旋转立方结构，给出其离散运动模型，推导出运动空间求解算法。为降低重构规划问题的不确定性和复杂程度，采用分层规划策略，将规划任务分解为设计中间构型的上层规划和求解实现中间构型移动方式的下层规划，每层规划内部独立进行求解。设计了利用Kuhn-Munkres算法实现上层规划的重构规划算法，使中间构型具有较小的结构跨度，特别适合在轨自重构的重构规划问题求解。仿真结果表明了所提规划策略和所设计规划算法的可行性和有效性。     

惯性参数不确定的自由漂浮空间机器人自适应控制研究

针对自由漂浮空间机器人系统惯性参数不确定问题,提出一种笛卡儿空间内的自适应轨迹跟踪控制方法。采用扩展机械臂模型建立了自由漂浮空间机器人关节空间动力学方程,进而推导笛卡儿空间中的自由漂浮空间机器人动力学方程。在基于逆动力学法的自由漂浮空间机器人自适应控制器设计中,利用标称控制器离线固定控制参数与补偿控制器在线补偿方法,既可以保证惯量矩阵可逆,又可以使控制参数实时估计。采用Lyapunov方法的稳定性分析表明系统是稳定且渐进收敛的。最后,应用该控制方法对两杆平面自由漂浮空间机器人进行了仿真研究。仿真结果显示自由漂浮空间机器人末端执行器在笛卡儿空间具有良好的轨迹跟踪能力。     

基于TOPSIS算法的数据中继任务动态优先级设置方法

针对中继卫星系统资源分配中的数据中继任务优先级设置问题开展研究,提出动态优先级评价方法,打破现有基于预设固化时段完成冲突消解的任务规划模式.综合考虑用户、需求,以及任务重要性等因素,建立任务优先级两级评价指标体系.其中,刚性优先级用于度量资源申请的必要性,柔性优先级用于维护资源分配的公平性,同时促进资源使用的合理性.详细列举了各项指标的量化模型,给出了柔性指标综合计算算法.在实验分析中,通过大量数据统计,测试了所提方法的可行性和有效性.     

欠驱动机器人的动力学耦合奇异研究

欠驱动机械臂的运动只能从动力学水平进行控制,从动关节的运动是通过主动关节的动力学耦合间接控制的。主、被动关节之间的动力学耦合特征与机械臂关节空间的位形有关,因此在欠驱动机械臂运动过程中可能发生动力学耦合奇异,某些被动关节的运动变得不可控。从关节空间和操作空间两个角度分析了欠驱动机械臂的动力学耦合问题,给出从以上两种工作空间度量系统动力学耦合的指标。提出一种基于输入变量非线性变换的滑模变结构控制方法,用于实现欠驱动机械臂操作空间中的连续轨迹控制。通过平面二连杆欠驱动机械臂和只有一个主动关节的平面三连杆欠驱动机械臂进行了仿真,仿真结果证明提出的控制方法是可行的。