快递分拣机器人控制系统的设计

为提高快递分拣效率,设计了一种基于OpenMV机器视觉模块的快递分拣机器人控制系统。在这一控制系统中,通过机器视觉技术实现快递件的轮廓识别、定位、扫码及分类,将STM32单片机作为运动控制核心,外接传感器感知机器人的状态,基于串口与机器视觉模块双向通信,实现对放置在地面的快递件进行自动分拣。通过制作样机验证了设计的合理性与可行性。     

Effect of practice on similar and dissimilar skills in patient transfer through training with a robot patient

With the number of hospital stays increasing, nurses require more training to handle a variety of patients. However, time for training in nursing schools is limited, and students lack the opportunity to practice on a diverse variety of patients. Using a robot to simulate actual patients, this study observes the learning transfer effect of practice on practice-similar and practice-dissimilar skills from one patient to another, and investigates which types of practice suit which kinds of training. An experiment was conducted by administering a pre-test, practice, a post-test, and a transfer test to two groups (N?=?8), each with different practice-related skills. The evaluation used a checklist covering required skills that were either similar or dissimilar across groups, depending on their practice. The effect of practice can be observed through a comparison of skills similar to one group but dissimilar to the other. The results show that practice facilitates learning transfer on similar skills but not, or to a lesser degree, on dissimilar skills. Furthermore, if skills needed to handle given symptoms are unfamiliar or inaccessible to students, practice related to those symptoms should be emphasized through simulated training with robots.     

Adaptive force–environment estimator for manipulators based on adaptive wavelet neural network

This study focuses on the accurate tracking control and sensorless estimation of external force disturbances on robot manipulators. The proposed approach is based on an adaptive Wavelet Neural Network (WNN), named Adaptive Force-Environment Estimator (WNN-AFEE). Unlike disturbance observers, WNN_AFEE does not require the inverse of the Jacobian transpose for computing the force, thus, it has no computational problem near singular points. In this scheme, WNN estimates the external force disturbance to attenuate its effects on the control system performance by estimating the environment model. A Lyapunov based design is presented to determine adaptive laws for tuning WNN parameters. Another advantage of the proposed approach is that it can estimate the force even when there are some parametric uncertainties in the robot model, because an additional adaptive law is designed to estimate the robot parameters. In a theorem, the stability of the closed loop system is proved and a general condition is presented for identifying the force and robot parameters. Some suggestions are provided for improving the estimation and control performance. Then, a WNN-AFEE is designed for a planar manipulator as an example, and some simulations are performed for different conditions. WNN_AFEE results are compared attentively with the results of an adaptive force estimator and a disturbance estimator. These comparisons show the efficiency of the proposed controller in dealing with different conditions.     

Non-kinematic calibration of a six-axis serial robot using planar constraints

This paper describes a non-kinematic calibration method developed to improve the accuracy of a six-axis serial robot, in a specific target workspace, using planar constraints. Simulation confirms that the stiffness of the robot, as well as its kinematic parameters, can be identified. An experimental validation shows that the robot's accuracy inside the target workspace is significantly enhanced by reducing the maximum distance errors from 1.321 mm to 0.274 mm. The experimental data are collected using a precision touch probe, which is mounted on the flange of a FANUC LR Mate 200iC industrial robot, and a high precision 9-in. granite cube. The calibration method makes use of a linear optimization model based on the closed-loop calibration approach using multi-planar constraints. A practical validation approach designed to reliably evaluate the robot's accuracy after calibration is also proposed.     

Tool-Center-Point control of the KAI manipulator using constrained QP optimization

The KAI manipulator is a four joint mobile manipulator, which will be used within the German road clearance package to investigate improvised explosive devices and ordnance from within an armored vehicle. To improve handling of the manipulator, a Tool-Center-Point (TCP) control is implemented. By using constrained quadratic optimization (cQP) it is possible to allow for the control of the manipulator within three different operating spaces. The QP is formulated to account for constraints in the joint angular rates and TCP velocities, as well as additional velocity constraints, e.g. on the movement of the center of mass of the manipulator. The proposed algorithm is able to handle redundant as well as non redundant manipulator kinematics. By using an efficient QP solver the algorithm can be used within a real-time trajectory generation scheme. The performance of the algorithm is demonstrated using simulation results and validated by measurements of the TCP control.     

“感知与人机交互”教学实践与PBL模式探索

机器人工程是在国家新工科发展战略背景下为了适应机器人专业人才需求而新近创建的专业。本文依托东南大学机器人工程专业教学体系，介绍了“感知与人机交互”课程的教学实践，探索了PBL教学模式在本门课程中的应用。具体介绍了课程教学内容设置、PBL教学方案例设计及存在问题分析等，可为自动化类机器人工程专业的相关课程教学实践提供参考。     

A literature survey of the robotic technologies during the COVID-19 pandemic

Since the late 2019, the COVID-19 pandemic has been spread all around the world. The pandemic is a critical challenge to the health and safety of the general public, the medical staff and the medical systems worldwide. It has been globally proposed to utilise robots during the pandemic, to improve the treatment of patients and leverage the load of the medical system. However, there is still a lack of detailed and systematic review of the robotic research for the pandemic, from the technologies’ perspective. Thus a thorough literature survey is conducted in this research and more than 280 publications have been reviewed, with the focus on robotics during the pandemic. The main contribution of this literature survey is to answer two research questions, i.e. 1) what the main research contributions are to combat the pandemic from the robotic technologies’ perspective, and 2) what the promising supporting technologies are needed during and after the pandemic to help and guide future robotics research. The current achievements of robotic technologies are reviewed and discussed in different categories, followed by the identification of the representative work’s technology readiness level. The future research trends and essential technologies are then highlighted, including artificial intelligence, 5 G, big data, wireless sensor network, and human-robot collaboration.     

工业机器人

介绍了我国工程机械行业开展机器人化研究的现状,并对喷浆机器人、压路机器人、隧道凿岩机器人等的研究开发情况逐一进行了介绍。