A human–robot interface for mobile manipulator

This paper presents a remote manipulation method for mobile manipulator through operator’s gesture. In particular, a track mobile robot is equipped with a 4-DOF robot arm to grasp objects. Operator uses one hand to control both the motion of mobile robot and the posture of robot arm via scheme of gesture polysemy method which is put forward in this paper. A sensor called leap motion (LM), which can obtain the position and posture data of hand, is employed in this system. Two filters were employed to estimate the position and posture of human hand so as to reduce the inherent noise of the sensor. Kalman filter was used to estimate the position, and particle filter was used to estimate the orientation. The advantage of the proposed method is that it is feasible to control a mobile manipulator through just one hand using a LM sensor. The effectiveness of the proposed human–robot interface was verified in laboratory with a series of experiments. And the results indicate that the proposed human–robot interface is able to track the movements of operator’s hand with high accuracy. It is found that the system can be employed by a non-professional operator for robot teleoperation.     

Indoor Positioning System Using Axis Alignment and Complementary IMUs for Robot Localization

An indoor positioning method for robots is presented to improve the precision of displacement measurement using only low-cost inertial measurement units(IMUs).Firstly,a high-fidelity displacement estimation for linear motion is proposed.A new robot motion model is designed as well as an axis alignment that only uses a single axis of the accelerometer.The integral error of velocity is eliminated by a new subsection calculation method.Two complementary IMUs are combined by assigning them different weights to obtain high accuracy displacement results.Secondly,an orientation estimation based on a fusion filter for the steering motion is proposed.Experiments show that the proposed method significantly improves the accuracy of linear motion measurement and is effective for the indoor positioning of a robot.     

基于三维环境模型的启发式路径规划算法

针对多自由度机器人手臂在未知环境中实时避障的问题,提出了一种基于环境信息的连杆机器人实时路径规划方法。采用笛卡尔空间内的障碍物检测信息建立了障碍物的空间模型,并依据该模型设计一种基于启发式规则的机器人路径规划算法。该算法不断猜测和修正路径,通过模糊推理得到下一位姿点,通过曲线拟合得到到达该位姿点的路径。在Matlab下利用机器人工具箱建立了PUMA560型机器人的运动学模型,并在运动空间设置障碍物,对该算法进行仿真分析,分析结果说明所提出的路径规划算法可以在较短时间内完成避障运动,具有较好的实时性,同时运动关节的角度变化曲线比较平滑,运动中冲击力较小,这些特点使其便于在实际工程中使用。     

Evaluation of active wearable assistive devices with human posture reproduction using a humanoid robot*

This study proposes a quantitative evaluation method for assessing active wearable assistive devices that can efficiently support the human body. We utilize a humanoid robot to simulate human users wearing assistive devices owing to various advantages offered by the robot such as quantitative torque measurement from sensors and highly repeatable motion. In this study, we propose a scheme for estimating the supportive torques supplied by a device called stationary torque replacement. To validate the reliability of this evaluation method by using a humanoid robot, we conducted measurements of human muscular activity during assisted motion. Analysis of the measured muscle activity revealed that a humanoid robot closely simulates the actual usage of assistive devices. Finally, we showed the feasibility of the proposed evaluation method through an experiment with the humanoid robot platform HRP-4 and the Muscle Suit active assistive device. With the proposed method, the supportive effects of the assistive device could be measured quantitatively in terms of the static supportive torque acting directly on the body of a simulated human user.     

New evaluation framework for human-assistive devices based on humanoid robotics

This paper presents the new application of a humanoid robot as an evaluator of human-assistive devices. The reliable and objective evaluation framework for assistive devices is necessary for making industrial standards in order that those devices are used in various applications. In this framework, we utilize a recent humanoid robot with its high similarity to humans, human motion retargeting techniques to a humanoid robot, and identification techniques of robot’s mechanical properties. We also show two approaches to estimate supporting torques from the sensor data, which can be used properly according to the situations. With the general formulation of the wire-driven multi-body system, the supporting torque of passive assistive devices is also formulated. We evaluate a passive assistive wear ‘Smart Suit Lite (SSL)’ as an example of device, and use HRP-4 as the humanoid platform.     

外骨骼式遥操作主手设计及主从异构映射算法研究

为了更好地促进机器人适应复杂的遥操作任务,开发了能够精确获取人体上肢运动信息的外骨骼式遥操作主手,并通过异构映射算法,实现对6自由度协作机械臂的遥操作．首先,基于人体仿生结构,设计了可穿戴式8自由度外骨骼主手（臂部7自由度和手部1自由度）;其次,通过改进的D-H（Denavit-Hartenberg）方法建立遥操作系统的运动学模型,基于Matlab的机器人工具箱进行了工作空间仿真,并设计主从异构映射算法;最后,实验验证外骨骼主手在遥操作系统中的可操作性,以及工作空间异构映射算法的可行性．实验表明,外骨骼主手能够控制从端机械手臂,且保证末端位置和姿态一致,可在大范围工作空间内复现人体上肢精细运动,主从跟随误差达2 mm,工作空间类似于直径1.08 m的半球形．因此,可穿戴式的外骨骼主手使操作者能更加直观地参与到遥操作系统当中,辅助操作者更加高效地完成精细复杂任务．     

Reinforcement learning-based shared control for walking-aid robot and its experimental verification

A walking-aid robot is an assistive device for enabling safe, stable and efficient locomotion in elderly or disabled individuals. In this paper, we propose a reinforcement learning-based shared control (RLSC) algorithm for intelligent walking-aid robot to address existing control problems in cooperative walking-aid robot system. Firstly, the intelligent walking-aid robot and the human walking intention estimation algorithm are introduced. Due to the limited physical and cognitive capabilities of elderly and disabled people, robot control input assistance is provided to maintain tactile comfort and a sense of stability. Then, considering the robot’s ability to autonomously adapt to different user operation habits and motor abilities, the RLSC algorithm is proposed. By dynamically adjusting user control weight according to different user control efficiencies and walking environments, the robot can improve the user’s degree of comfort when using the device and automatically adapting to user’s behaviour. Finally, the effectiveness of our algorithm is verified by experiments in a specified environment.     

Study of the characteristics of random errors in measurements by MEMS inertial sensors

This paper considers a stochastic analysis of measurement errors in MotionNode inertial measurement units (IMUs). The sensors of this device are based on the microelectromechanical system (MEMS) technology. The use of the Allan variance algorithm for identifying the error’s nature and the stochastic modeling of this error make it possible to substantially reduce the measurement errors by sensors. Based on the results of this study, we elaborated a number of recommendations for increasing the efficiency of the use of MEMS inertial sensors for problems of the navigation of moving objects.     

Motion trajectory of human arms based on the dual quaternion with motion tracker

In this paper, we present an algorithm for human motion capture of the real-time motion trajectory of human arms based on wireless inertial 3D motion trackers. It aims to improve the accuracy of inertial motion captures and quickly reconstruct some human movements. To evaluate the performance of the proposed dual quaternion algorithm, we present the prototype design. The wireless inertial measurement system and Kinect device are introduced simultaneously in capturing human motion. The dual quaternion algorithm incorporates features of the quaternion rotation and translation. So the singular points of Euler angles can be avoided. Dual quaternion algorithm and DCM(direction cosine matrix) are used to reconstruct human arm movements respectively. Compared with the computing speed in Matlab, the speed of the dual quaternion is faster than it of DCM. To the end, we propose a 3D ADAMS human robotic model for simulating the motion trajectory using dual quaternion algorithm. The results show that the dual quaternion can achieve capabilities of a positive DCM solving, which completed between body segments rotating and translating the coordinate system transformation. Also it can effectively drive in real-time a human model to animate movement, and provide a good algorithm.     

Assistive robot application based on an RFID control architecture and a wireless EOG interface

This paper describes an assistive robot application that combines a portable wireless interface based on electrooculography (EOG) and Radiofrequency Identification (RFID) technology. This assistive application is aimed at handicapped users who suffer from a severe motor disability. To that end, a realistic application has been designed. It consists of an environment in which users can bring a glass and a water bottle closer with only the help of their eye movement using a real robot arm. RFID will be used as a support to the EOG interface in a shared control architecture by storing information of the objects in tags placed on the scene. Five volunteers tested the assistive robot application. The results obtained show that all of them were able to finish the tests in a suitable time and the results improved with practice and training. This proves that the assistive robot application can be a feasible way to help handicapped users.     

Walking algorithm for a robotic transfemoral prosthesis capable of walking pattern recognition and posture stabilization

This paper describes a walking pattern generation algorithm for a robotic transfemoral prosthesis that is synchronized with the walking motion of a transfemoral amputee, and posture stabilization for ground adaptation and maintaining balance on inclined grounds. The developed robotic transfemoral prosthesis in this study has a knee joint and ankle roll/pitch joints for walking on complex slopes. The walking motion data obtained from the motion capture system are used as the standard walking pattern data to accurately imitate the inherent gait of the wearer. Walking intention, percent of gait cycle (PGC), and walking stride are predicted through two inertial sensors attached at both thighs, and the joint angles of the robotic transfemoral prosthesis are then generated in real-time from the PGC and the standard walking pattern data. Additionally, variable impedance control and zero moment point (ZMP) control are carried out with a force/torque sensor for posture stabilization against variable ground slopes, and ground slope compensation and disturbance rejection are also done with the use of inertial sensors at the foot and shank. Consequently, the performance of the walking pattern generation algorithm and posture stabilization control was verified through walking experiments of an author on an inclined treadmill.     

Reactive navigation of underwater mobile robot using ANFIS approach in a manifold manner

Learning and self-adaptation ability is highly required to be integrated in path planning algorithm for underwater robot during navigation through an unspecified underwater environment. High frequency oscillations during underwater motion are responsible for nonlinearities in dynamic behavior of underwater robot as well as uncertainties in hydrodynamic coefficients. Reactive behaviors of underwater robot are designed considering the position and orientation of both target and nearest obstacle from robot’s current position. Human like reasoning power and approximation based learning skill of neural based adaptive fuzzy inference system (ANFIS) has been found to be effective for underwater multivariable motion control. More than one ANFIS models are used here for achieving goal and obstacle avoidance while avoiding local minima situation in both horizontal and vertical plane of three dimensional workspace. An error gradient approach based on input-output training patterns for learning purpose has been promoted to spawn trajectory of underwater robot optimizing path length as well as time taken. The simulation and experimental results endorse sturdiness and viability of the proposed method in comparison with other navigational methodologies to negotiate with hectic conditions during motion of underwater mobile robot.     

Robust human position estimation in cooperative robotic cells

Robots are increasingly present in our lives, sharing the workspace and tasks with human co-workers. However, existing interfaces for human-robot interaction / cooperation (HRI/C) have limited levels of intuitiveness to use and safety is a major concern when humans and robots share the same workspace. Many times, this is due to the lack of a reliable estimation of the human pose in space which is the primary input to calculate the human-robot minimum distance (required for safety and collision avoidance) and HRI/C featuring machine learning algorithms classifying human behaviours / gestures. Each sensor type has its own characteristics resulting in problems such as occlusions (vision) and drift (inertial) when used in an isolated fashion. In this paper, it is proposed a combined system that merges the human tracking provided by a 3D vision sensor with the pose estimation provided by a set of inertial measurement units (IMUs) placed in human body limbs. The IMUs compensate the gaps in occluded areas to have tracking continuity. To mitigate the lingering effects of the IMU offset we propose a continuous online calculation of the offset value. Experimental tests were designed to simulate human motion in a human-robot collaborative environment where the robot moves away to avoid unexpected collisions with de human. Results indicate that our approach is able to capture the human’s position, for example the forearm, with a precision in the millimetre range and robustness to occlusions.     

基于双轴旋转框架捷联惯性组件快速标定方法研究

现场条件下惯组的标定精度及标定速度直接影响惯性导航系统的使用.基于双轴旋转框架的捷联惯组快速标定法,将带有旋转框架的惯组安装在载体上,只需一次通电后控制双轴框架合理转位,实现惯组误差参数的快速辨识.结果表明6位置快速标定法,可以满足捷联惯组现场标定精度要求且在30 min内即可完成惯组标定,尤其是降低了现场标定时对高精度三轴转台的依赖,极大地提高了器件测试的灵活性.     

Control of an exoskeleton robot arm with sliding mode exponential reaching law

Robots are now working not only in human environments but also interacting with humans, e.g., service robots or assistive robots. A 7DoFs robotic exoskeleton MARSE-7 (motion assistive robotic-exoskeleton for superior extremity) was developed as an assistive robot to provide movement assistance and/or ease daily upper-limb motion. In this paper, we highlight the nonlinear control of MARSE-7 using the modified sliding mode exponential reaching law (mSMERL). Conventional sliding control produces chattering which is undesired for this kind of robotic application as it causes damage to the mechanical structure. Compared to conventional sliding control, our approach significantly reduces chattering and delivers a high dynamic tracking performance. The control architecture was implemented on a field-programmable gate array (FPGA) in conjunction with a RT-PC. In experiments, trajectory tracking that corresponds to typical passive arm movement exercises for single and multi joint movements were performed to evaluate the performance of the developed robot and the controller. Experimental results demonstrate that the MARSE-7 can effectively track the desired trajectories.     

基于多传感器的机器人遥操作人机交互系统

为了增强机器人人机交互系统的自然性,提出了基于多种传感器的非接触式人机交互系统设计方案,系统通过检测操作者手部动作和手部位置姿态的变化实现机器人的遥操作。研制了肌电传感器,获取手臂上一对拮抗肌上的表面肌电信号,并以此来判断机器人操作者的部分手部动作;利用Kinect体感设备和惯性测量单元获取手臂三维位置和姿态角信息。通过网络将人手的动作及位置姿态发送至机器人控制系统,以完成对机器人的控制。系统综合多种传感器的优点,极大减小了传统接触式交互方式对操作者运动范围的限制,实现了自然交互,实验表明了其有效性。     

基于简化三维线性倒立摆模型的模糊控制射门算法

针对双足机器人传统射门算法存在仅适用于固定射门角度和射门姿态的问题,提出了一种基于简化三维线性倒立摆模型的模糊控制射门算法,用于实现多角度、多姿态的射门。首先利用简化三维线性倒立摆模型规划出零力矩点(ZMP)轨迹和质心轨迹;其次在双腿支撑相对双足机器人进行射门角度和姿态的调整,同时利用贝塞尔曲线规划出游动腿的轨迹;最后利用模糊控制算法精确地规划出双足机器人的射门轨迹。实验部分利用NAO机器人仿真平台验证了本文提出射门算法的性能,并与其它射门算法进行了比较。最后将实物NAO机器人用于全过程与多角度的实际射门实验,验证了本文提出射门的算法可行性与准确性。     

基于北斗/iNEMO惯性模块的机器人运动姿态解算方法

基于北斗/iNEMO惯性模块研究了一种组合式机器人运动姿态测量系统和解算方法。设计了以ARM为核心的嵌入式组合姿态解算平台,通过四元数法和卡尔曼滤波技术,对iNEMO惯性组件测量数据进行融合,进而在高动态环境中实时解算出机器人的运动姿态。同时,以北斗接收机输出的1PPS上升沿脉冲作为数据融合的同步信号,并利用其输出的导航信息辅助iNEMO惯性模块实现精对准。测试结果验证了设计方案的可行性和正确性,为机器人姿态解算提供了一种高精度、高稳定性、小体积、低功耗的解决方案。     

Human Arm Motion Tracking by Inertial/Magnetic Sensors Using Unscented Kalman Filter and Relative Motion Constraint

Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the measurement covariance matrix in such a way that the filter implements gyroscopes when large accelerations are involved. The proposed algorithm was evaluated experimentally by an optical tracking system as the ground truth reference. The results showed the effectiveness and good performance of the proposed algorithm.     

基于分级规划策略的拟人机械臂仿人运动规划算法研究

为使拟人机械臂具有高精度的仿人运动,提出一种通过触发条件和分级规划策略 的仿人运动新方法。将人臂运动过程离散为不同运动阶段,在每一个运动阶段都有与之对应的 规划层,在不同的规划层中,拟人机械臂的运动特点不同。利用各自的特点建立不同规划层下 的运动模型及臂姿预测指标,对拟人机械臂臂姿进行预测。最后,以NAO 机器人为实验平台, 比较所提方法与最小势能法(MTPE)的静态臂姿与动态臂姿预测,并与运动捕捉系统(OptiTrack) 采集的真实人臂运动数据进行比较。实验表明,该方法具有较小的静态臂姿和动态臂姿预测误 差,能使拟人机械臂产生高度逼真的仿人运动。