基于分布式控制系统的空间大型末端执行器抓捕策略

针对空间大型机械臂冈其关节和臂杆柔性带来的抓捕前定位问题,为一种具有柔性捕获接口的新型末端执行器设计了分布式控制系统,并建立了以捕获环收缩速度为主要控制对象的抓捕策略,可实现稳定且高效的抓捕.其中,该控制系统由传感器单元、上层控制单元和3个模块化的底层驱动单元组成.传感器单元和底层驱动单元集成在末端执行器内部,采集系统...     

空间大型末端执行器抓捕容差优化及其仿真

为了使空间大型末端执行器的抓捕操作性能得到最大程度的发挥,不同于传统的从机构设计角度得到末端执行器固定抓捕容差的方法,本文从优化设计学的角度出发,根据末端执行器的工作过程及其原理,将抓捕容差划分为捕获容差和拖动容差两部分,通过分析影响大型末端执行器抓捕容差的结构因素,分别建立了末端执行器捕获容差和拖动容差的数学优化模型,并基于线性加权法和惩罚函数法获得了抓捕容差最优值(128.58mm,128.58 mm,100 mm,15.12,15.12,16.32)T,同时得到了末端执行器本体相对应的结构参数.最终,采用仿真研究方法进行了抓捕容差优化及抓捕性能实验研究.实验结果验证了理论分析的正确性,证明本文提出的末端执行器数学优化模型合理,优化算法正确.     

一种空间大容差末端执行器设计方案与仿真分析

根据大型空间机械臂及其在轨服务操作任务的特点,提出了大型空间机械臂末端执行器大容差和软捕获的基本性能要求,同时给出了实现上述基本性能的方法.在此基础上,提出了一种具有大容差性能的机械臂末端执行器设计方案.为了准确获得该类末端执行器的性能指标,完成了该类末端执行器的详细设计,也为后期的动力学仿真分析提供准确的3维模型.最...     

空间大型末端执行器柔性钢丝绳的建模与捕获动力学

针对大容差软捕获这一空间捕获操作的重要准则,研制了基于钢丝绳的末端执行器大容差柔性捕获机构.针对钢丝绳具有较大柔性,在窄间应用环境下难于快速连续建模控制的问题,提出丁柔性钢丝绳的离散控制模型,解决了钢丝绳的建模问题.通过钢丝绳的离散模型,分析了末端执行器钢丝绳柔性机构捕获空间自由飞行载荷舱的动力学问题.实验证明钢丝绳模...     

空间机器人最优能耗捕获目标的自适应跟踪控制

提出了一种能够引导末端执行器以期望速度跟踪目标的轨迹规划方法。该方法可以实现避障并满足关节限制要求。基于轨迹规划方法,设计了一种利用自由飘浮空间机器人跟踪与捕获章动自旋卫星的自适应控制策略。此外,该控制策略还考虑了最优能耗、测量误差和优化误差。首先,为了使执行器的跟踪误差和机械臂的能耗最小,将空间机器人的控制策略描述为一个关于关节速度、力矩和避障距离的不等式约束优化问题。然后,推导出一个系数为下三角矩阵的显式状态方程,并对目标函数进行解耦和线性化。设计了一种关节速度和力矩分段优化方法去代替传统的凸二次规划方法求解最优问题,这种方法具有较高的计算效率。最后,利用李雅普诺夫稳定性理论验证了所提控制方法的收敛性。     

一种自移动空间机械臂末端执行器的研制

针对中小型自移动空间机械臂在轨操作和"换位行走"的任务需求,研制了一种小型化、大容差、高刚度可靠连接的末端执行器及其相应的目标适配器.末端执行器采用单一驱动实现捕获、拉紧锁合、解锁和电连接器插拔等多种功能.考虑捕获容差条件及锁合性能要求,对末端执行器的关键机构参数进行设计.通过ADAMS建立虚拟样机,对捕获容差及锁合的功能性能进行验证.最后通过样机实验对末端执行器的功能进行验证,验证了设计的可行性及仿真的准确性.     

三手指空间机器人末端执行器的柔顺抓握策略

空间机器人在抓握物体时,末端执行器与目标物体之间因接触碰撞而产生的扰动力可能会造成机械臂抖动和位姿改变,甚至将日标物体弹出捕获区,造成捕获失败,针对这一问题,首先介绍了哈尔滨工业大学(HIT)自行研制的三于指窄间机器人末端执行器,对末端执行器抓握日标物体过程中的碰撞扰动力进行了分析,提出了一种柔顺抓握策略以削弱抓握目标...     

柔性机械臂基于观测的逆动力学轨迹跟踪控制

本文探讨了稳定逆动力学与基于观测的状态误差反馈镇定器集成实现柔性机械臂 末端轨迹跟踪的控制策略．基于观测器可以充分利用由稳定逆动力学生成的理想状态轨迹信 息,实现全状态误差的反馈镇定以消除末端轨迹跟踪的扰动误差．     

空间机器人捕获运动目标的协调规划与控制方法

针对目标以任意轨迹运动且其轨迹可能与``有保证工作空间'不相交的问题, 提出了空间机器人捕获运动目标的协调规划与控制方法. 首先, 根据手眼视觉测量数据, 预测目标的运动路径, 由此确定空间机器人对目标的最优交会姿态及最佳捕获臂型; 其次, 规划基座姿态及机械臂关节角的轨迹; 最后, 采用协调控制的方法, 实现空间机器人系统对运动目标的最优捕获(以最优交会姿态及最佳捕获臂型对目标进行捕获). 仿真结果表明了该方法的有效性.     

基于机器视觉与单片机结合的机械臂抓取系统

抓取规划和控制是机械臂抓取系统中的难点.为了有效的解决这两个问题,本文提出一种基于机器视觉和单片机相结合的机械臂抓取系统.首先利用前期视觉测量成果对目标定位,然后设计了一种软件接口将目标表面三维信息进行可视化,并通过人为经验手动选择一个良好的抓取点;再结合逆运动学求解和轨迹规划算法,利用单片机驱动舵机使机械臂末端执行器...     

结合IMask R-CNN的绳驱机械臂视觉抓取方法研究

绳驱超冗余机械臂具有灵活性强、工作空间大等特点,在航天活动中可替代宇航员进行各种航空作业.以空间飞行器在轨维修为研究背景,模拟其实验环境,设计了一套基于RGB-D的可移动绳驱超冗余机械臂定位抓取系统.首先改进了Mask R-CNN算法,在保证检测精度的同时降低模型尺寸,通过Intel RealSense D435 i采集图像输入到目标检测模型得到目标的类别和位置信息,进一步利用自适应末端位置更新算法递推机械臂的正逆运动学模型,并结合轨迹规划完成目标的三维空间定位和抓取.实验结果表明,改进后的Mask R-CNN算法能在保证精度的情况下有效地降低模型尺寸,抓取系统的逆运动学求解速度快,具有较好的定位精度,能够有效地完成飞行器抓取的任务.     

空间机器人目标捕获的自适应规划

与地面固定基座机器人不同的是,空间机器人的运动学方程中含有动力学参数。在执行目标捕获任务时,目标动力学参数的不精确会给空间机器人的规划带来致命的影响。针对目标捕获后动力学参数不精确情况下的关节空间规划问题,在建立了自由飘浮空间机器人运动学模型的基础上,给出了雅可比矩阵及其动量守恒方程中的惯性参数以及惯性参数的组合参数线性化的具体形式,提出了一种关节空间的自适应规划方法。以平面二连杆空间机器人为研究对象进行仿真验证。结果表明,所提出的自适应规划方法可以有效降低惯性参数不精确给运动规划带来的影响,为空间机器人执行目标捕获等任务时提供了任务空间内精确轨迹跟踪的能力。     

Performance evaluation of a wearable inertial motion capture system for capturing physical exposures during manual material handling tasks

With a long-term goal of improving quantification of physical exposures in the workplace, this study examined the ability of a commercially available inertial motion capture (IMC) system in quantifying exposures during five different simulated manual material handling tasks. Fourteen participants repeated all these tasks in three 20 min sequential time blocks. Performance of the IMC system was compared against an optical motion capture (OMC) system (‘gold standard’) in terms of joint angles, angular velocities and moments at selected body parts. Though several significant changes in performance over time were found, the magnitudes of these were relatively small and may have limited practical relevance. The IMC system yielded peak kinematic values that differed by up to 28% from the OMC system. The IMC system, in some cases, incorrectly reflected the actual extremity positions of a participant, and which can cause relatively large errors in joint moment estimation. Given the potential limitations, practical recommendations are offered and discussed.

Practitioner Summary: Use of an inertial motion capture system can advance the quantification of physical exposures in situ. Results indicate a good potential capacity for capturing physical exposure data in the field for an extended period, while highlighting potential limitations. Future system application can help provide better understandings of dose-exposure relationships.     

Localization in time and space for wireless sensor networks: An efficient and lightweight algorithm

In many applications that use Wireless Sensor Networks (WSNs), detected events need to be localized in both time and space. As a result, sensor nodes need to have precisely synchronized clocks as well as to be localized in a common spatial reference system. While synchronization and localization algorithms have been proposed to solve these problems independently, in this work we propose to combine both synchronization and localization into a single problem that we refer to as the time–space localization problem. We then propose a novel and efficient time–space localization algorithm for wireless sensor networks which we refer to as the Lightness algorithm. Our proposed algorithm not only takes advantage of the additional hardware resources required by the positioning mechanism in order to improve the performance and scalability of synchronization, but also benefits from the additional communication needed by the synchronization mechanism in order to decrease positioning errors. We also present an extensive set of experiments to evaluate the performance of our algorithm. Our results indicate clearly that our proposed scheme is scalable while keeping a low synchronization error and a low communication overhead. Our results also indicate that the additional packets needed to compute clocks’ drift have the ability to decrease the positioning errors to almost one third of the initial positioning.     

Underwater space suit performance assessments part 1: Motion capture system development and validation

This study aimed to develop and deploy a novel motion capture system capable of measuring space suit kinematics in an underwater test environment. The system was built using off-the-shelf, dive-rated hardware and open source software tools. The new system performance was validated by comparing the measurement outcome to a reference motion capture system in a dry-land condition. Measurement errors, defined as the linear distances of the marker position measurements between the developed and reference system, were 1.9 cm root-mean-square error (RMSE) with a 50-percentile error of 1.3 cm and a 95-percentile error of 3.6 cm. Measurement error tended to increase with motion speed. Similarly, the error showed a slight tendency of increasing with the distance from the center of the calibrated capture volume. However, the trend was not clearly identifiable. A second metric of system accuracy performance was calculated by assessing the wand length. The system was deployed underwater and tested for space suit kinematic assessments. Given the speed and range of space suit motions underwater, the measurement error of the developed system underwater was estimated to be approximately 1.39 cm and the wand length estimation error had a RMSE of 0.67 cm with a 50-percentile error of 0.51 cm and a 95-percentile error of 0.92 cm. Overall, the new system showed reliable and acceptably accurate kinematic measurements comparable to a common dry land motion capture system and can provide usable suit performance metrics in a simulated microgravity environment.Relevance to industryAn underwater motion capture system was developed using off-the-shelf equipment. The new system was deployed to assess the kinematic mobility of space suits. The system can offer an inexpensive solution where traditional motion capture system may not be applicable.     

伪卫星室内导航定位系统研究和设计

GPS(Global Position System)伪卫星是一种用来生成并发射类似GPS信号的装置,在卫星信号脆弱的情况下,伪卫星可以作为GPS辅助增强,也可以在GPS信号完全失效的情况下用来建立独立定位系统;基于伪卫星室内独立定位的需求,提出一种低成本伪卫星的设计方案,通过频谱仪和接收机能够稳定捕获和跟踪到设计的伪卫星信号,作为室内组网的硬件基础;分析和推导SPP定位算法,将接收机输出的伪距和载波相位等测量信息进行定位处理,获得定位结果;并对伪卫星室内定位进行组网布局和设计,分析实验过程中的各组网组成部分;最后,在实验室内进行静态和动态定位实验,验证能够捕获和跟踪伪卫星信号,并得出厘米级的静态定位结果。     

一种光学式运动捕捉系统下的物体运动数据捕捉方法研究

多相机视觉运动捕捉系统能通过捕捉标记点的空间坐标来获得运动物体的运动学参数,文中提出了一种基于多相机运动捕捉系统下的通用物体运动数据捕捉方法;首先根据3个标记点组成固定模型获取物体运动过程中对应标记点的瞬时坐标,然后通过向量法求解出被测物体在运动过程中各采集点对应的物体位姿,然后通过卡尔曼滤波方法消除运动捕捉过程中的系统和环境误差的影响,获得平滑的物体位姿运动轨迹,并根据滤波数据计算出物体在各采集点对应的速度、加速度、角速度、角加速度;最后基于协作机器人进行物体的运动数据捕捉实验,验证了所提出物体运动数据捕捉方法的正确性。     

Constructing Human Motion Manifold With Sequential Networks

This paper presents a novel recurrent neural network-based method to construct a latent motion manifold that can represent a wide range of human motions in a long sequence. We introduce several new components to increase the spatial and temporal coverage in motion space while retaining the details of motion capture data. These include new regularization terms for the motion manifold, combination of two complementary decoders for predicting joint rotations and joint velocities and the addition of the forward kinematics layer to consider both joint rotation and position errors. In addition, we propose a set of loss terms that improve the overall quality of the motion manifold from various aspects, such as the capability of reconstructing not only the motion but also the latent manifold vector, and the naturalness of the motion through adversarial loss. These components contribute to creating compact and versatile motion manifold that allows for creating new motions by performing random sampling and algebraic operations, such as interpolation and analogy, in the latent motion manifold.