Safe planning for human‐robot interaction

This paper presents a strategy for improving the safety of human‐robot interaction by minimizing a danger criterion during the planning stage. This strategy is one part of the overall methodology for safe planning and control in human‐robot interaction. The focus application is a hand‐off task between an articulated robot and an inexpert human user. Two formulations of the danger criterion are proposed: a criterion assuming independent safety‐related factors, and a criterion assuming mutually dependent factors. Simulations of the proposed planning strategy are presented for both 2D and 3D robots. The results indicate that a criterion based on scaled mutually dependent factors such as the robot inertia and the human robot distance generates safe, feasible paths for interaction. © 2005 Wiley Periodicals, Inc.     

Effects of movement speed and predictability in human–robot collaboration

Human–robot collaboration (HRC) is characterized by a spatiotemporal overlap between the workspaces of the human and the robot and has become a viable option in manufacturing and other industries. However, for companies considering employing HRC it remains unclear how best to configure such a setup, because empirical evidence on human factors requirements remains inconclusive. As robots execute movements at high levels of automation, they adapt their speed and movement path to situational demands. This study therefore experimentally investigated the effects of movement speed and path predictability of an industrial collaborating robot on the human operator. Participants completed tasks together with a robot in an industrial workplace simulated in virtual reality. A lower level of predictability was associated with a loss in task performance, while faster movements resulted in higher‐rated values for task load and anxiety, indicating demands on the operator exceeding the optimum. Implications for productivity and safety and possible advancements in HRC workplaces are discussed.     

Robust disturbance estimation for human–robotic comanipulation

External forces affect the dynamics of load‐carrying robot devices. The knowledge of such disturbances is generally needed for control purposes. However, direct disturbance measurement using force sensors is not always possible. This paper introduces a force estimator for force‐sensor‐less robotic manipulators. The algorithm is based on the knowledge of the dynamics of the robotic device, whereas mass of the load is typically unknown. Using this algorithm, low‐frequency external forces can be estimated robustly even for quasi‐statically time‐varying and uncertain loads. Experiments validate the proposed strategy in practice. Moreover, the applicability of the estimation algorithm is further illustrated by using it in a human–robot comanipulation setup in which the robot is providing additional coordinated forcing to alleviate human effort needed to manipulate the robot. Copyright © 2013 John Wiley & Sons, Ltd.     

A bio‐inspired approach for regulating and measuring visco‐elastic properties of a robot arm

This work focuses on interaction control of robot manipulators in unstructured environments, with special regard for situations of unpredictable contact/noncontact transitions. It is basically addressed to those environments where a high level of robot adaptability is required and no information on the geometry of the environment is available. By pointing out the main limitations of standard interaction control schemes in managing situations of contact/noncontact transitions, this paper proposes a new control solution that is inspired by the biological model of motor control in voluntary movements. It consists of a combination of a feedforward loop and a proportional‐derivative plus gravity compensation control in the feedback loop. The control law is named coactivation‐based compliance control in the joint space since a unique function, called coactivation function, is evaluated for regulating robot visco‐elasticity in an unpredictably variable environment. It resumes the mechanism of adjustable visco‐elastic properties acting on the agonist and antagonist muscles of a human arm. The work also proposes a methodology for evaluating performance of interaction control schemes that is based on stiffness graphical representation through ellipses. The method replicates the experimental setup used in neuroscience to measure stiffness in human limbs. It is regarded as a powerful tool for evaluating robot behavior over space and time, since it allows both a visual representation of stiffness variation during motion and a quantitative measure of robot performance. It is shown how the method can be used to evaluate a control scheme and how it can provide indications to improve a control law. In this paper, an application to the standard compliance control in the joint space and the coactivation‐based compliance control is presented. © 2005 Wiley Periodicals, Inc.     

Telerobotic visual servoing

This paper addresses the problem of integrating the human operator with autonomous robotic visual tracking and servoing modules. A CCD camera is mounted on the end-effector of a robot and the task is to servo around a static or moving rigid target. In manual control mode, the human operator, with the help of a joystick and a monitor, commands robot motions in order to compensate for tracking errors. In shared control mode, the human operator and the autonomous visual tracking modules command motion along orthogonal sets of degrees of freedom. In autonomous control mode, the autonomous visual tracking modules are in full control of the servoing functions. Finally, in traded control mode, the control can be transferred from the autonomous visual modules to the human operator and vice versa. This paper presents an experimental setup where all these different schemes have been tested. Experimental results of all modes of operation are presented and the related issues are discussed. In certain degrees of freedom (DOF) the autonomous modules perform better than the human operator. On the other hand, the human operator can compensate fast for failures in tracking while the autonomous modules fail. Their failure is due to difficulties in encoding an efficient contingency plan.     

Reaching for redundant arms with human-like motion and compliance properties

This work proposes a redundant arm torque controller for reaching, guaranteeing desired completion time and accuracy requirements without the need for trajectory planning and prior knowledge of robot dynamics. The proposed controller is designed based on the prescribed performance control methodology and it is a reaching regulator in which the target pose for the hand acts as an attractor for the arm. It provides configuration consistency in return motions and hand and joint velocity smoothness. Its use in an admittance control scheme given measurements or estimates of external forces is also proposed providing active compliance capabilities in robot–environment interactions. Simulation studies for a 5dof human arm-like robot and experiments with a 7dof arm are performed to verify the approach and demonstrate the proposed controller’s performance.     

人手到灵巧手的运动映射实现

本文研究主从操作中人手到灵巧手的运动映射．提出了一种基于虚拟关节和虚拟手指的关节空间运动映射方法，实现了人手和灵巧手的三维运动仿真．以数据手套为人机接口，在虚拟环境下，通过直观地比较映射效果，验证了映射算法．     

A human–robot interface using particle filter,Kalman filter,and over-damping method

This paper presents a novel human–manipulator interface which copies the hand motion to control a manipulator. In the proposed interface, an inertial measurement unit is used to measure the orientation of the human hand, and a 3D camera is employed to locate the human hand using the Camshift algorithm. Although the position and the orientation of the human can be obtained from two sensors, the measurement errors increase over time due to the noise of the devices and the tracking errors. Therefore, particle filter and Kalman filter are used to estimate the position and the orientation of the human hand. Due to the limitations of the perceptive and the motor, human operator cannot accomplish the high-precision manipulation without any assistance. An over-damping method is employed to assist the operator to improve the accuracy and reliability in determining the postures of the manipulator. The human–manipulator interface system was experimentally tested in a lab environment, and the results indicate that such an interface can successfully control a robot manipulator even when the operator is not an expert.     

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.     

Human‐robot collaborative site‐specific sprayer

Spraying pesticides is a key element of agriculture worldwide, since 30% to 35% of crop losses can be prevented when harmful insects and diseases are eliminated by applying pesticides. Site‐specific spraying can help reduce pesticide application; however, target detection is limited due to the complex agricultural environment. This paper presents a human‐robot collaborative sprayer designed for site‐specific targeted spraying. The robotic sprayer platform, the framework, and tools for the robotic sprayer to collaborate with a remote human operator for the target detection and spraying tasks are detailed. An experiment to evaluate the elements of the collaborative human‐robot framework working in sync was designed, implemented, and evaluated. The collaborative spraying system shows a 50% reduction of sprayed material. The experiment also proves the feasibility of human‐robot collaboration for the complex task of spraying specific targets considering both the True Positive (TP) and False Positive (FP) rates.     

Robotic grasping and manipulation through human visuomotor learning

A major goal of robotics research is to develop techniques that allow non-experts to teach robots dexterous skills. In this paper, we report our progress on the development of a framework which exploits human sensorimotor learning capability to address this aim. The idea is to place the human operator in the robot control loop where he/she can intuitively control the robot, and by practice, learn to perform the target task with the robot. Subsequently, by analyzing the robot control obtained by the human, it is possible to design a controller that allows the robot to autonomously perform the task. First, we introduce this framework with the ball-swapping task where a robot hand has to swap the position of the balls without dropping them, and present new analyses investigating the intrinsic dimension of the ball-swapping skill obtained through this framework. Then, we present new experiments toward obtaining an autonomous grasp controller on an anthropomorphic robot. In the experiments, the operator directly controls the (simulated) robot using visual feedback to achieve robust grasping with the robot. The data collected is then analyzed for inferring the grasping strategy discovered by the human operator. Finally, a method to generalize grasping actions using the collected data is presented, which allows the robot to autonomously generate grasping actions for different orientations of the target object.     

Adaptive position and orientation regulation for the camera‐in‐hand problem

This paper considers the camera‐space position and orientation regulation problem for the camera‐in‐hand problem via visual serving in the presence of parametric uncertainty associated with the robot dynamics and the camera system. Specifically, an adaptive robot controller is developed that forces the end‐effector of a robot manipulator to move such that the position and orientation of an object are regulated to a desired position and orientation in the camera‐space, despite parametric uncertainty throughout the entire robot‐camera system. An extension is also provided that illustrates how slight modifications can be made to the camera‐in‐hand control law to achieve adaptive position and orientation tracking of the end‐effector in the camera‐space for a fixed‐camera configuration. Simulation results are provided to illustrate the performance of the adaptive, camera‐in‐hand controller. © 2005 Wiley Periodicals, Inc.     

满足不同交互任务的人机共融系统设计

人与机器人共同协作的灵活生产模式已经成为工业成产的迫切需求,因此,近年来人机共融系统方面的研究受到了越来越多关注.设计并实现了一种满足不同交互任务的人机共融系统,人体动作的估计和机器人的交互控制是其中的关键技术.首先,提出了一种基于多相机和惯性测量单元信息融合的人体姿态解算方法,通过构造优化问题,融合多相机下的2D关节检测信息和所佩戴的惯性测量单元测量信息,对人体运动学姿态进行优化估计,改善了单一传感器下,姿态信息不全面以及对噪声敏感的问题,提升了姿态估计的准确度.其次,结合机器人的运动学特性和人机交互的特点,设计了基于目标点跟踪和模型预测控制的机器人控制策略,使得机器人能够通过调整控制参数,适应动态的环境和不同的交互需求,同时保证机器人和操作人员的安全.最后,进行了动作跟随、物品传递、主动避障等人机交互实验,实验结果表明了所设计的机器人交互系统在人机共融环境下的有效性和可靠性.     

Perceptive whole‐body planning for multilegged robots in confined spaces

Legged robots are exceedingly versatile and have the potential to navigate complex, confined spaces due to their many degrees of freedom. As a result of the computational complexity, there exist no online planners for perceptive whole‐body locomotion of robots in tight spaces. In this paper, we present a new method for perceptive planning for multilegged robots, which generates body poses, footholds, and swing trajectories for collision avoidance. Measurements from an onboard depth camera are used to create a three‐dimensional map of the terrain around the robot. We randomly sample body poses then smooth the resulting trajectory while satisfying several constraints, such as robot kinematics and collision avoidance. Footholds and swing trajectories are computed based on the terrain, and the robot body pose is optimized to ensure stable locomotion while not colliding with the environment. Our method is designed to run online on a real robot and generate trajectories several meters long. We first tested our algorithm in several simulations with varied confined spaces using the quadrupedal robot ANYmal. We also simulated experiments with the hexapod robot Weaver to demonstrate applicability to different legged robot configurations. Then, we demonstrated our whole‐body planner in several online experiments both indoors and in realistic scenarios at an emergency rescue training facility. ANYmal, which has a nominal standing height of 80 cm and a width of 59 cm, navigated through several representative disaster areas with openings as small as 60 cm. Three‐meter trajectories were replanned with 500 ms update times.     

PD‐like controllers for delayed bilateral teleoperation of manipulators robots

This paper proposes a compensated PD‐like controller for delayed bilateral teleoperation of a manipulator robot. The scheme has a PD‐like remote controller, a damping into the master, and a compensation strategy. The proposed compensation removes part of potential energy of the user's command depending on the difference between the situation on the remote site and the situation as perceived by the human operator. In addition, the stability of the delayed teleoperation system is analyzed, and a comparison based on experiments is carried out in order to analyze the advantages of using the proposed compensation. Finally, results of a bilateral teleoperation including the proposed control scheme, where the master and slave exchange information by using a low‐cost connection of mobile Internet, are shown. Copyright © 2014 John Wiley & Sons, Ltd.     

Experimental Testing of a Gauge Based Collision Detection Mechanism for a New Three‐Degree‐of‐Freedom Flexible Robot

The use of flexible robots can be easily justified in two main cases: (1) when the weight of the robot has to be minimized and (2) when collisions between the robot and the environment are foreseen, since a flexible, lightweight robot implies less impact energy. The position control of these robots has already been analyzed in previous communications. However, the second of these cases justifying the use of flexible robots requires further consideration, leading to the development of a force controller. Inmost up to date analysis the force control is studied beginning from a known contact point at a given collision time. In a more realistic approach, however, an accurate detection of the collision would be needed prior to dealing with the force control. After developing a reliable position controller for a three‐degree‐of‐freedom flexible robot using strain gauges placed over the robot structure, in this paper we deal with the possibility of carrying out the collision detection for the same prototype. This has been easily achieved by analyzing some estimated signals such as tip position and tip velocity. However, a complete analysis of the information obtained with the sensors has been required to obtain those estimates and a signal processing scheme had to be devised for a previous filtering of the original signals from the sensors (encoders and strain gauges). This work has been carried out as a first step towards the position/force control. Experimental results on a three‐degree‐of‐freedom flexible arm prototype are presented to verify how well this method performs. © 2003 Wiley Periodicals, Inc.     

基于人机交互的移动服务机器人导航系统

针对目前全自主移动机器人尚难实现的问题,基于人机结合的思想研制了由操作者、人机交互平台和移动机器人组成的“人—机—环境”一体化移动机器人导航系统．介绍了该系统的结构组成,阐述了系统导航策略,详细分析了人机交互、人机协作、移动机器人位姿预测及基于扩展卡尔曼滤波的位姿校正方法．设计了导航系统界面,通过在室内真实环境下的导航实验,验证了该“人—机—环境”一体化移动机器人导航系统的有效性．     

Fusing Visual and Inertial Sensing to Recover Robot Ego‐motion

A method for estimating mobile robot ego‐motion is presented, which relies on tracking contours in real‐time images acquired with a calibrated monocular video system. After fitting an active contour to an object in the image, 3D motion is derived from the affine deformations suffered by the contour in an image sequence. More than one object can be tracked at the same time, yielding some different pose estimations. Then, improvements in pose determination are achieved by fusing all these different estimations. Inertial information is used to obtain better estimates, as it introduces in the tracking algorithm a measure of the real velocity. Inertial information is also used to eliminate some ambiguities arising from the use of a monocular image sequence. As the algorithms developed are intended to be used in real‐time control systems, considerations on computation costs are taken into account. © 2004 Wiley Periodicals, Inc.     

Efficient behavior learning in human–robot collaboration

We present a novel method for a robot to interactively learn, while executing, a joint human–robot task. We consider collaborative tasks realized by a team of a human operator and a robot helper that adapts to the human’s task execution preferences. Different human operators can have different abilities, experiences, and personal preferences so that a particular allocation of activities in the team is preferred over another. Our main goal is to have the robot learn the task and the preferences of the user to provide a more efficient and acceptable joint task execution. We cast concurrent multi-agent collaboration as a semi-Markov decision process and show how to model the team behavior and learn the expected robot behavior. We further propose an interactive learning framework and we evaluate it both in simulation and on a real robotic setup to show the system can effectively learn and adapt to human expectations.