全自动机器人在涤纶长丝生产中的应用

"机器换人"是荣盛石化股份有限公司在化纤生产中的一次设备革新,也是将传统生产逐步过渡到智能化生产的一次大胆尝试。介绍了从德国引进的高端工业自动化落丝包装一体化设备,通过全自动机器人的运用,实现从落丝—输送—检测—中间立体仓储—包装等全自动一体化功能,帮助企业提高了自动化程度,节省了人工成本,提高了生产效益。     

Utility of stereoscopic displays for indirect-vision driving and robot teleoperation

The effectiveness of an active shutter-glasses stereoscopic display (SD) and a passive polarised SD was evaluated in a live robot-teleoperation task and a simulated indirect-vision driving task in various terrains. Overall, participants completed their tasks significantly faster with the SDs in three-dimensional (3D) mode than with the SDs in the baseline 2D mode. They also navigated more accurately with the SDs in 3D mode. When the effectiveness of the two types of SDs was examined separately, results showed that the active shutter-glasses SD resulted in faster responses and task completion times than the passive polarised SD, though most of the differences failed to reach statistical significance. Perceived workload when interacting with the two SD systems did not differ significantly between the active versus passive display types or between the 3D and 2D modes of operation; however, participants reported more severe discomfort after interacting with the passive polarised SD.     

基于运动相关皮层电位握力运动模式识别研究

面向基于脑-机接口（Brain-computer interface,BCI）的脑-机交互控制（Brain-machine interaction control,BMIC）——直接脑控机器人,提出一种新的左、右手握力运动参数范式,在该范式下探索左、右手握力运动相关皮层电位/运动相关电位（Movement-related potentials,MRPs）的时域特征表示并识别握力运动模式.在涉及左、右手4个不同任务的实验中采集了11个健康被试的脑电信号,任务期间要求被试以2种握力变化模式之一完成自愿握力运动,每种任务随机重复30次.不同握力任务之间具有显著差异的运动相关电位特征用于识别握力运动模式.分别用基于核的Fisher线性判别分析和支持向量机识别4个不同的握力运动任务.研究结果进一步证实运动相关电位可以表征握力运动规划、运动执行和运动监控的脑神经机制过程.基于核的Fisher线性判别分析和支持向量机分别获得24±4%和21±5%的平均错误分类率.最小误分类率是12%,所有被试平均最小误分类率为20.9±5%.与传统的仅仅识别参与运动的肢体类型以及识别单侧肢体运动参数的研究相比,本研究可望为脑-机交互控制/脑控机器人接口提供更多的力控制意图指令,奠定了后续的对比研究基础.     

多模式无线传感机器人的研究与设计

所设计机器人主要具有无线测温、测距、自动避障以及远距离遥控4种工作模式。设计分为两个分系统:遥控端分系统和驱动控制端分系统,两个分系统采用半双工通信方式。主要阐述驱动控制端的硬件和软件设计。其硬件平台采用MSP430F5438A作为MCU,CC1100作为无线传输模块。在设计中还增加了三轴位移模块,保证了机器人运动的稳定性。通过将机器人的灵活运动性与无线传感的实时可控性相结合,大大增加了产品的实用性和使用范围。     

SHeRo: Scalable hexapod robot for maintenance,repair, and operations

Improper maintenance, repair, and operations of societal centric structures can lead to catastrophic failures that drastically affect global economy, the environment, and everyday life. Due to the remote, cramped and highly irregular environmental nature of these structures, routine manual procedures and operations can be rather tedious, dangerous, and hazardous for humans. Automating maintenance, repair, and operations removes human workers from having to crawl within highly cluttered and constrained spaces, breathing in stale air mixed with fumes from welding or particulate from repair work, and provides higher reliability and consistency in the repair work. This paper introduces SHeRo, a scalable hexapod robot designed for maintenance, repair, and operations within remote, inaccessible, irregular, and hazardous environments. The scalability of the design enhances traditional hexapod robot designs by incorporating two prismatic joints into each leg. A detailed discussion on the design and realization of SHeRo is provided. An analysis on the stability and workspace of SHeRo is presented and a dynamic criterion is developed to integrate the concepts of robot stability and constant orientation workspace into a stable workspace. The analytical solution of the lateral stable workspace of SHeRo is derived along with a metric for comparing stable workspace between different robot configurations. A simulated demonstration and two physical experimental demonstrations are presented showing the advantage of introducing scalability into the hexapod robot design along with the workspace enhancement and flexibility of the scalable hexapod robot.     

Attention allocation for decision making queues

We consider the optimal servicing of a queue with sigmoid server performance. There are various systems with sigmoid server performance, including systems involving human decision making, visual perception, human–machine communication and advertising response. Tasks arrive at the server according to a Poisson process. Each task has a deadline that is incorporated as a latency penalty. We investigate the trade-off between the reward obtained by processing the current task and the penalty incurred due to the tasks waiting in the queue. We study this optimization problem in a Markov decision process (MDP) framework. We characterize the properties of the optimal policy for the MDP and show that the optimal policy may drop some tasks; that is, may not process a task at all. We determine an approximate solution to the MDP using the certainty-equivalent receding horizon optimization framework and derive performance bounds on the proposed receding horizon policy. We also suggest guidelines for the design of such queues.     

A binary approximating method for graspable region determination of biped climbing robots

For a biped pole-climbing robot (BiPCR) with grippers, it is an essential demand to determine the target grasp configuration for climbing and transiting between poles, with the graspable region as a priori knowledge. The graspable region on the target pole is critically important for climbing path planning and motion control. To efficiently compute the graspable region for a BiPCR, we propose a novel binary approximating method in this paper. This method may also be applied to generate the three-dimensional (3-D) workspace of a manipulator with constant orientation. The grasping problem and the concept of graspable region for a BiPCR are first introduced. The binary approximating method and the corresponding algorithms are then presented to generate the graspable region. Additional constraints on a biped climbing robot with five degrees of freedom (DoFs) are presented as a supplement to the algorithm. A series of comprehensive simulations are conducted with the five-DoF and six-DoF climbing robots to verify the effectiveness of the proposed method. Finally, the dexterity of biped climbing robots with different DoFs is discussed.     

Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.     

Design of a slave arm of a surgical robot system to estimate the contact force at the tip of the employed instruments

Acquisition of the contact force at the instrument tip can enable better performance, e.g. transparency of the haptic feedback in the surgical robot systems. It is, however, difficult to measure the contact force directly due to technical limitations in attaching sensors to the tip of the instruments. This paper proposes a method to estimate the forces by installing the sensors away from the instrument tip. The proposed method employs specially designed mechanical parts of the slave robot, i.e. a slider cover plate for the z-axis translational force along the insertion direction, and docking clamps for the rotational pivot torques around the fulcrum point. Strain gauges are attached to specially designed places with enhancing shapes. The simulation results of the force estimation are presented to confirm the strain concentration area. The proposed method is validated with quantitative experimental results. Calibrated weights are determined upon the comparison of the strain value with a calibrated 6-axis force/torque sensor. The percentage error in the force calibration is about 5~8% calculated by the root mean square error (RMSE) of force-sensing performance. In addition, it can be computed by considering only the bending phase of each sensor although the hysteresis is observed from the calibration graph.