Shenyang Institute of Automation,Chinese Academy Of Sciences
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基于数字孪生的人机协同固体燃料整形系统及建立方法
No full text本发明涉及虚拟现实领域，尤其涉及基于数字孪生的人机协同固体燃料整形系统及建立方法，包括以下步骤：1)对整形场景模型进行构建；2)建立固体燃料模型；3)建立机械臂数字孪生仿真模型，并在机械臂数字孪生仿真模型上设置功能接口，并与力反馈手柄连接；4)将力反馈手柄与实体机械臂连接，实现机械臂数字孪生仿真模型与实体机械臂的同步运行；5)数字孪生系统通过力控制模块处理，实时改变实体机械臂的运动状态；6)机械臂数字孪生仿真模型和固体燃料模型在整形场景模型下的三维场景重构；7)重复步骤4)‑6)。本发明比较传统遥感操作作业，孪生系统提供的模拟视角能全方位查看操作可以让操作者及时对操作过程中突发情况做出调整
一种用于精密运动控制的异构计算加速方法
No full text本发明涉及精密运动控制及异构加速领域，为对控制周期要求为50us及以上的精密运动控制提供一种用于精密运动控制的异构计算加速方法。可实现基于固定周期精密运动控制的异构计算加速。方法包括：控制器、异构计算板卡及被控对象等。控制器中包含控制算法模型和内核驱动模块。异构计算板卡包括计算核心、结果缓存、发送缓存、接收缓存、全局时钟。控制器与异构计算板卡通过PCIE总线互联，异构计算板卡与被控对象通过IO总线互联。基于本发明的异构计算加速方法，可以使系统的计算工作更加高效运行，系统实时性稳定性进一步提高
无人艇的运动路径规划方法、装置、终端设备及存储介质
No full text本发明公开了一种无人艇的运动路径规划方法、装置、终端设备及存储介质，方法包括：获取无人艇的目标位姿状态以及起始位姿状态；目标位姿状态包括：目标坐标以及目标航向角；起始位姿状态包括：起始坐标以及起始航向角；构建无人艇航行区域的栅格地图；从目标位姿状态进行反向搜索，确定无人艇从目标位姿状态至栅格地图中每个栅格的花费，将无人艇从目标位姿状态至栅格地图中每个栅格的花费作为每个栅格的启发值，生成启发值栅格地图；根据启发值栅格地图、起始位姿状态、目标位姿状态及各位姿状态的轨迹单元，生成无人艇从起始位姿状态至目标位姿状态的运动路径；每一位姿状态所对应的轨迹单元根据每一位姿状态以及预设的无人艇动力学模型生成
一种基于力感知测量的高效精密研抛轨迹优化方法
No full text针对零件表面的研磨抛光过程，提出一种基于力感知测量的高效精密研抛轨迹优化方法，具体包括以下步骤：以待加工工件三维模型为依据，对零件进行理论加工轨迹规划；控制机器人按照规划轨迹进行运动，采用力感知测量的方式记录每个控制点对应的型差信息，轨迹点余量信息计算，得到表面实际加工点位置补偿信息；根据去除工具和去除材料等工艺参数进行零件表面研磨抛光工艺处理；控制过程中采用渐变量去除的方式，保证加工的效率和精度。与传统方法相比，利用本发明测量的加工轨迹具有打磨加工后型面一致和光顺等优点，且省去了更换测量工具和数据传输、分析等过程，十分简单快捷。实验结果和分析表明该方法能够提高零件的研磨抛光表面质量
甘蔗收获机割台仿形装置
No full text本实用新型属于甘蔗收获机技术领域，特别涉及一种甘蔗收获机割台仿形装置。包括触地部件、连接套筒、固定连接板、横梁及角位移传感器，其中固定连接板连接在横梁上，连接套筒可转动地安装在固定连接板上，触地部件与连接套筒连接，角位移传感器安装在连接套筒的一侧，角位移传感器用于采集触地部件的转动角度变化，从而检测地形高度的起伏变化。本实用新型可以实现甘蔗收获机对作业地形高度的实时性检测，能够将割台仿形装置模块化，安装简易，使用寿命长
一种锁钩式展开锁定机构
No full text本实用新型涉及太阳电池阵列帆板技术领域，特别涉及一种锁钩式展开锁定机构。该机构包括母铰链、锁钩、公铰链、铰链轴及片簧，其中母铰链和公铰链通过铰链轴铰接，公铰链上设有凸起结构；锁钩铰接在母铰链上，且与公铰链上的凸起结构接触；片簧设置于母铰链上，且位于锁钩的外侧；当母铰链和公铰链处于展开状态时，片簧通过弹力推动锁钩与公铰链锁紧。本实用新型为单板或转动关节相对较少的太阳电池阵结构与机构而设计，实现帆板的展开和锁定，同时具有结构简单、成本低、锁紧精度可调、锁紧精度高的特点
Triggering grabbing type multi-cavity sampling mechanism
No full text本发明涉及航天工程中样品采集技术领域，特别涉及一种触发抓取式多腔采样机构。该机构包括转位组件、采样腔、转盘组件及开腔组件，其中转位组件的输出端与转盘组件连接，并且驱动转盘组件转动；转盘组件上沿周向设有多个采样腔；开腔组件设置于转位组件的下方，用于开启与开腔组件相对应的一个采样腔。本发明通过触发抓取式多腔采样机构的运动，在采样腔与星体表面接触后触发，从而在扭转弹簧的驱动下采样腔门关闭，达到抓取星表样品的目的，对于星体表面一些凹陷的地形有一定的适应能力
Privacy-Preserving Publicly Verifiable Databases
No full textVerifiable databases (VDB) enables the data owner to outsource a huge unencrypted database to the powerful but untrusted cloud such that any client could later retrieve the database and check whether the cloud returns valid records or not. To the best of our knowledge, there is no prior work considering privacy. Besides, they assume that the data owner and the client are fully trusted while they may be semi-honest in the real world. To address these problems, we propose a new primitive called privacy-preserving publicly verifiable database (PPVDB), which not only guarantees the integrity of the queried result but also leaks no information. At the end of this protocol, the client can check whether the cloud returns a valid result and learns the queried result but nothing else about the database. Besides, the cloud learns nothing about the database and the query, and the data owner does not know which item that the client has queried. Motivated by the comparison among some strawman solutions, we incorporate verifiable computation for the polynomial with oblivious pseudorandom function to construct a PPVDB scheme, which is the first VDB scheme providing stronger security against the malicious cloud and the semi-honest client and data owner.</p
Vibration suppression of collaborative robot based on modified trajectory planning
No full textPurpose The paper aims to reduce the low-frequency resonance and residual vibration of the robot during the operation, improve the working accuracy and efficiency. A reduced weight and large load-to-weight ratio can improve the practical application of a collaborative robot. However, flexibility caused by the reduced weight and large load-to-weight ratio leads to low-frequency resonance and residual vibration during the operation of the robot, which reduces the working accuracy and efficiency. The vibrations of the collaborative robot are suppressed using a modified trajectory-planning method. Design/methodology/approach A rigid-flexible coupling dynamics model of the collaborative robot is established using the finite element and Lagrange methods, and the vibration equation of the robot is derived. Trajectory planning is performed with the excitation force as the optimization objective, and the trajectory planning method is modified to reduce the vibration of the collaborative robot and ensure the precision of the robot terminal. Findings The vibration amplitude is reduced by 80%. The maximum torque amplitude of the joint before the vibration suppression reaches 50 N center dot m. After vibration suppression, the maximum torque amplitude of the joint is 10 N center dot m, and the resonance phenomenon is eliminated during the operation process. Consequently, the effectiveness of the modified trajectory planning method is verified, where the vibration and residual vibration in the movement of the collaborative robot are significantly reduced, and the positioning accuracy and working efficiency of the robot are improved. Originality/value This method can greatly reduce the vibration and residual vibration of the collaborative robot, improve the positioning accuracy and work efficiency and promote the rapid application and development of collaborative robots in the industrial and service fields.</p
Learning Cognitive Map Representations for Navigation by Sensory-Motor Integration
No full textHow to transform a mixed flow of sensory and motor information into memory state of self-location and to build map representations of the environment are central questions in the navigation research. Studies in neuroscience have shown that place cells in the hippocampus of the rodent brains form dynamic cognitive representations of locations in the environment. We propose a neural-network model called sensory-motor integration network model (SeMINet) to learn cognitive map representations by integrating sensory and motor information while an agent is exploring a virtual environment. This biologically inspired model consists of a deep neural network representing visual features of the environment, a recurrent network of place units encoding spatial information by sensorimotor integration, and a secondary network to decode the locations of the agent from spatial representations. The recurrent connections between the place units sustain an activity bump in the network without the need of sensory inputs, and the asymmetry in the connections propagates the activity bump in the network, forming a dynamic memory state which matches the motion of the agent. A competitive learning process establishes the association between the sensory representations and the memory state of the place units, and is able to correct the cumulative path-integration errors. The simulation results demonstrate that the network forms neural codes that convey location information of the agent independent of its head direction. The decoding network reliably predicts the location even when the movement is subject to noise. The proposed SeMINet thus provides a brain-inspired neural-network model for cognitive map updated by both self-motion cues and visual cues.</p