Variable admittance time-delay control of an upper limb rehabilitation robot based on human stiffness estimation

This paper proposes a new variable admittance time-delay control strategy based on human stiffness estimation for improving the effectiveness of robot-assisted cooperative rehabilitation training. This control strategy is developed and implemented on a planar upper limb rehabilitation robot. Given the minimum-jerk-based desired trajectories of human hand position, in the developed control strategy, a time-delay approximator is utilized to estimate the external disturbances and modeling errors without exact knowledge of dynamics parameters, a sliding mode admittance controller is applied to obtained objective admittance characteristics, and an iterative optimization algorithm is used to estimate human arm stiffness and adjust human-robot interaction compliance. The closed-loop stability of the proposed control method is demonstrated via Lyapunov function theory. Experimental investigations involving ten subjects are conducted to validate the feasibility of the proposed control scheme. The experimental results show that the interaction compliance during cooperative rehabilitation training can be accurately adjusted based on selected admittance parameters and human arm stiffness, and it contributes to satisfying the specific training requirements of patients with different weakness levels and promoting the effectiveness of the robot-assisted training.     

钢丝绳传动在航空光学遥感器上的应用

针对某航空光学遥感器扫描组件和消旋组件需以高精度同步旋转的要求,提出一种通过双电机驱动,采用独立的位置环和速度环控制的钢丝绳精密传动方法。首先,详细介绍了钢丝绳精密传动的结构形式和控制方法,并简要分析了钢丝绳的传动刚度,最后,通过实验对钢丝绳精密传动的精度进行测试,同时分析了预紧力和负载力对精度的影响。实验结果表明:本钢丝绳精密传动系统实现了扫描组件和消旋组件旋转同步精度0.03°,旋转速度为5°/s时稳速精度达1.5%,满足设计要求。实验结果验证了本钢丝绳精密传动应用方法的可行性,为钢丝绳精密传动在航空光学遥感器上的应用提供了一种新的方法。     

Dance Step Estimation Method Based on HMM for Dance Partner Robot

The main purpose of this paper is to realize an effective human-robot coordination with physical interaction. A dance partner robot has been proposed as a platform for it. To realize the effective human-robot coordination, recognizing human intention would be one of the key issues. This paper focuses on an estimation method for dance steps, which estimates a next dance step intended by a human. In estimating the dance step, time series data of force/moment applied by the human to the robot are used. The time series data of force/moment measured in dancing include uncertainty such as time lag and variations for repeated trials because the human could not always exactly apply the same force/moment to the robot. In order to treat the time series data including such uncertainty, hidden Markov models are utilized for designing the dance step estimation method. With the proposed method, the robot successfully estimates a next dance step based on human intention     

Performance-based assistance control for robot-mediated upper-limbs rehabilitation

Clinical research results demonstrated that robot-mediated training for the recovery of subjects after the stroke had the benefit of being able to carry out high-intensity repetitive and task-oriented tasks, which could effectively facilitate the rehabilitation effect. However, these subjects may have different training requirements as the disability levels vary from subject to subject at different stages of rehabilitation. Therefore, to meet the rehabilitation training needs of subjects in different rehabilitation stages, a performance-based assistance control strategy for safe robot-mediated therapy is proposed in this paper. The strategy contains three training modes that are switched by the trajectory tracking error, the zero interaction force mode (ZIF), assist-as-needed (AAN) mode, and restriction interaction region (RIR) mode. In ZIF mode, the subject can freely refer to their motion trajectory, and the robot will only offer fixed assistance only when the subject is slacking. In AAN mode, the robot would offer a variable level of assistance force by adjusting the stiffness coefficient to assist subjects in accordance with their motor abilities. To assure safety, a sizable assisting force is applied in RIR mode. To validate and evaluate the effectiveness and performance of the proposed assistance control strategy, a set of task-oriented continuous movement experiments based on an end-effector robot-mediated training system were performed by five able-bodied subjects. The preliminary experiment results demonstrated that the proposed control strategy works properly and could provide corresponding assistance and adjust the working modes according to the subject's motor performance. It was found that the robot provided more assistance as the increasing trajectory tracking error led to a decrease in motor performance. Additionally, adaptive adjustment of the stiffness coefficient allowed the proposed assistance control strategy to induce more active effort. It's worth noting that the parameters of the proposed strategy may be personalized and adjusted for different subjects to satisfy various requirements.     

Fault-tolerant control system of flexible arm for sensor fault by using reaction force observer

In recent years, control system reliability has received much attention with increase of situations where computer-controlled systems such as robot control systems are used. In order to improve reliability, control systems need to have abilities to detect a fault (fault detection) and to maintain the stability and the control performance (fault tolerance). In this paper, we address the vibration suppression control of a one-link flexible arm robot. Vibration suppression is realized by an additional feedback of a strain gauge sensor attached to the arm besides motor position. However, a sensor fault (e.g., disconnection) may degrade the control performance and make the control system unstable at its worst. In this paper, we propose a fault-tolerant control system for strain gauge sensor fault. The proposed control system estimates a strain gauge sensor signal based on the reaction force observer and detects the fault by monitoring the estimation error. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault-mode controller so as to maintain the stability and the control performance. We apply the proposed control system to the vibration suppression control system of a one-link flexible arm robot and confirm the effectiveness of the proposed control system by some experiments.     

Design and experiments on an inflatable link robot with a built-in vision sensor

Soft robots and manipulators with inflatable links possess inherent safety characteristics that make them a very interesting choice for tasks requiring human-robot interaction. However, they may face important challenges in their performance due to low structural stiffness. Accurate positioning of the end effector may prove a difficult task due to limitations in gravity compensation, or due to the occurrence of oscillations during motion, especially in the absence of precise information about the payload that is being manipulated. In this paper a novel approach to the design and control of a robot with an inflatable link is proposed, where the link assumes the triple role of compliant structural element, touch sensor, and active mechanism to adjust the performance of vibration control algorithms. For this, a vision sensor is placed inside the link to provide information about the structural deformation. The sensor is used to measure the tip displacement, and also to detect contact of the link surface with the surrounding environment. The concept was implemented on a two-joint rigid manipulator with a single inflatable link. Experiments on vibration control and contact detection of the inflatable link are reported where the control system was able to significantly reduce tip oscillations, including when a payload was added to the tip. The robot was also able to make binary detection of contact between the inflatable link and the user, and change its operation mode accordingly.     

Design & characterization of a bio-inspired 3-DOF Tactile/Force sensor and implementation on a 3-DOF decoupled parallel mechanism for human-robot interaction purposes

This paper presents the design and implementation of a Tactile/Force sensor which has been used on a 3-DOF decoupled parallel mechanism for Human-Robot Interaction purposes.The sensor, called HexaTactile, is a soft tactile sensor array based on six MEMS barometers, where each of them is covered by a silicone layer in the form of an incomplete pyramid. HexaTactile consists of six soft and highly sensitive tactile modules which are placed on six sides of a cube to allow simultaneous measurement of the force in the positive and negative directions along the x, y and z axes. Some of the advantages of this sensor can be regarded as its high precision, excellent linearity (coefficient of determination r²=0.99), low cost and low noise. The accuracy of the sensor is 0.01 N, within a range of 4 N and therefore HexaTactile can be suitably attached to a robot end-effector for human-robot interaction applications. Then, using the proposed force sensor some control scenarios, including fixed admittance control and active admittance control are applied for human-robot interaction purposes. From the experimental tests, it has been revealed that the active admittance control solved the drawbacks of fixed admittance control, for the considered case studies.     

Human-cable collision detection with a cable-driven parallel robot

This paper deals with human-cable collision detection with a Cable-Driven Parallel Robot (CDPR) and a control strategy to safely release the tension in the cable in contact with a human operator. The main purpose of this work is to contribute to the development of safety solutions allowing collaborative work between human and robot with CDPRs in production tasks. Using a geometric model of cable deformations under an external collision, a direct relationship is established between the initial cable tension, the collision force and the increase in cable tension. This relationship is validated experimentally with an ad-hoc test bench. Collision force levels are set to admissible values in order to prevent harm for human operators. A collision detection is then implemented on the 8-cable suspended CDPR CRAFT prototype using this method, continuously comparing the cable tensions measured by sensors with admissible cable tension increases. Using these results, an approach aiming at releasing a collided cable so as to minimize risks for operators and the environment of the robot is proposed with an adaptive control scheme, based on a progressive cable tension management once a collision is detected. This cable tension management is simulated and represented in the null space of CDPR wrench matrix. Feasibility domain of this tension management and alternative solutions outside of it are also discussed. This work contributes to the safety of collaborative CDPRs by determining a direct relationship between collision force and cable tensions in the event of a collision and by introducing a collision detection method.     

Fuzzy behavior integration and action fusion for robotic excavation

This paper discusses control behavior integration and bucket action fusion for excavation control of a robotic front-end-loader type machine. To utilize the experience and expertise from skilled human operators, a fuzzy-logic based control approach is developed. A hierarchical excavation control architecture decomposes excavation goals to tasks, then tasks to behaviors, and finally behaviors to actions. The excavation actions are primitive and can be executed directly by an excavation machine. Finite state machines are used to specify the coordination and integration of behaviors for task execution and actions for behavior implementation. A simple strategy for action fusion is proposed based on fuzzy logic reasoning and the COA defuzzification method. Finally, laboratory experiments are conducted using a PUMA 560 robot arm and a Zebra force/torque sensor in a simulated rock excavation environment. Experimental results indicate that the proposed approach in this paper has led to more efficient task execution than previous approaches     

Passive arbitration in adaptive shared control of robots with variable force and stiffness scaling

In mixed-initiative shared control, the final control command to the robot is a weighted sum of the commands from two or more agents (human operators or automatic control systems). In force controlled robots, scaling of forces without power-consistent scaling of velocities leads to loss of passivity of the overall system. In this work, we first pose the problem statement related to position drift, while using a state-of-the-art, passivity ensuring method for scaling of forces. We then formulate adaptive mixed-initiative shared control as an adaptive stiffness control approach. We ensure passivity of the adaptive stiffness controller with a novel, model-independent method. The salient features, benefits and limitations of the approach are emphasized through analyses, simulations and hardware experiments. The proposed approach is finally validated with a practical shared control task.     

Human-robot contact in the safeguarding space

In this paper, we discuss a human-robot (H-R) coexistent system which allows H-R contact actions in the safeguarding space mechanically bounded by the human pain tolerance limit. The first half of this paper describes our study on the evaluation of the human pain tolerance limit which determines an individual's safeguarding space. We also show the human-safety-oriented design of a robot. The robot is covered with a viscoelastic material to achieve both impact force attenuation and contact sensitivity, keeping within the human pain tolerance limit. The robot, with simple direct-drive (DD) motor torque detection and emergency stop capabilities, automatically stops whenever any severe H-R contact occurs. In the second half of the paper, we propose a more efficient H-R system, which allows H-R contact for improving work efficiency, as long as the contact does not exceed the human pain tolerance limit. For this purpose, a robot is controlled to reduce its velocity with high reliability at an incipient stage of its contact with a human. Through experiments, we demonstrate the validity and efficient utility of the safeguarding space. The first experiment verifies that the developed robot exerts a contact force less than the human pain tolerance limit establishing the safeguarding space. The second experiment comparatively shows the robot's velocity reduction to accept a safe contact with the human in the space     

Development and evaluation of interactive humanoid robots

We report the development and evaluation of a new interactive humanoid robot that communicates with humans and is designed to participate in human society as a partner. A human-like body will provide an abundance of nonverbal information and enable us to smoothly communicate with the robot. To achieve this, we developed a humanoid robot that autonomously interacts with humans by speaking and gesturing. Interaction achieved through a large number of interactive behaviors, which are developed by using a visualizing tool for understanding the developed complex system. Each interactive behavior is designed by using knowledge obtained through cognitive experiments and implemented by using situated recognition. The robot is used as a testbed for studying embodied communication. Our strategy is to analyze human-robot interaction in terms of body movements using a motion-capturing system that allows us to measure the body movements in detail. We performed experiments to compare the body movements with subjective evaluation based on a psychological method. The results reveal the importance of well-coordinated behaviors as well as the performance of the developed interactive behaviors and suggest a new analytical approach to human-robot interaction.     

Control design of a novel compliant actuator for rehabilitation robots

Rehabilitation robots have direct physical interaction with human body. Ideally, actuators for rehabilitation robots should be compliant, force controllable, and back drivable due to safety and control considerations. Series Elastic Actuators (SEA) offers many advantages for these applications and various designs have been developed. However, current SEA designs face a common performance limitation due to the compromise on the spring stiffness selection. This paper presents a novel compact compliant force control actuator design for portable rehabilitation robots to overcome the performance limitations of current SEAs. Our design consists of a servomotor, a ball screw, a torsional spring between the motor and the ball screw, and a set of translational springs between the ball screw nut and the external load. The soft translational springs are used to handle the low force operation, while the torsional spring with high effective stiffness is used to deal with the large force operation. It is a challenging task to design the controller for such a novel design as the control system needs to handle both the force ranges. In this paper, we develop the force control strategy for this actuator. First, two dynamical models of the actuator are established based on different force ranges. Second, we propose an optimal control with friction compensation and disturbance rejection which is enhanced by a feedforward control for the low force range. The proposed optimal control with feedforward term is also extended to the high force range. Third, a switching control strategy is proposed to handle a transition between low force and high force control. The mathematical proof is given to ensure the stability of the closed-loop system under the proposed switching control. Finally, the proposed method is validated with experimental results on a prototype of the actuator system and is also verified with an ankle robot in walking experiments.     

Neural network impedance force control of robot manipulator

The performance of an impedance controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and environment stiffness. The purpose of this paper is to improve the controller robustness by applying the neural network (NN) technique to compensate for the uncertainties in the robot model. NN control techniques are applied to two impedance control methods: torque-based and position-based impedance control, which are distinguished by the way of the impedance functions being implemented. A novel error signal is proposed for the NN training. In addition, a trajectory modification algorithm is developed to determine the reference trajectory when the environment stiffness is unknown. The robustness analysis of this algorithm to force sensor noise and inaccurate environment position measurement is also presented. The performances of the two NN impedance control schemes are compared by computer simulations. Simulation results based on a three-degrees-of-freedom robot show that highly robust position/force tracking can be achieved in the presence of large uncertainties and force sensor noise     

Estimation of elbow-induced wrist force with EMG signals using fast orthogonal search

In many studies and applications that include direct human involvement-such as human-robot interaction, control of prosthetic arms, and human factor studies-hand force is needed for monitoring or control purposes. The use of inexpensive and easily portable active electromyogram (EMG) electrodes and position sensors would be advantageous in these applications compared to the use of force sensors, which are often very expensive and require bulky frames. Multilayer perceptron artificial neural networks (MLPANN) have been used commonly in the literature to model the relationship between surface EMG signals and muscle or limb forces for different anatomies. This paper investigates the use of fast orthogonal search (FOS), a time-domain method for rapid nonlinear system identification, for elbow-induced wrist force estimation. It further compares the forces estimated using FOS with the forces estimated by MLPANN for the same human anatomy under an ensemble of operational conditions. In this paper, the EMG signal readings from upper arm muscles involved in elbow joint movement and sensed elbow angular position and velocity are utilized as inputs. A single degree-of-freedom robotic experimental testbed has been constructed and used for data collection, training and validation.     

Force control of a very lightweight single-link flexible arm based on coupling torque feedback

In this paper, a feedback control law is proposed for regulating the contact force exerted by a very lightweight single-link flexible manipulator when it comes into contact with a motionless object. This control law is based on a lumped-parameter model. The tracking of the desired contact force is obtained by using a feedback loop control of the coupling torque between the motor and the flexible arm. To achieve a good performance on the force control it is only necessary to measure the coupling torque at the root of the arm. Neither the contact force sensor nor the angular position sensor of the motor are used in the control method. A modified PID controller is proposed for this control law. In this work the force control problem is studied for both free and constrained motions of the flexible manipulator, and a collision detection algorithm is also described.     

HERMES - a versatile personal robotic assistant

We have developed a humanoid robot, HERMES, to study several key technologies that are important for personal robots, such as robot design, sensors and perception, locomotion, localization and navigation, manipulation, human-robot communication and interaction, adaptability and learning, system architecture and integration, and dependability. The robot's skill-based system architecture was derived from a qualitative model of human information processing and insights gained from psychological literature dealing with skill acquisition, human performance and motor learning. HERMES' system architecture, several of its skills and the design principles are introduced, and some experiments carried out with the real robot are presented, including a long-term test where HERMES served in a museum, far away from its home laboratory, for more than six months up to 12 hours per day. During this period the robot and its skills were regularly demonstrated to the public by nonexpert presenters. Also, HERMES interacted with the visitors, chatted with them in English, French and German, answered questions and performed services as requested by them.     

A Serial-Type Dual Actuator Unit With Planetary Gear Train: Basic Design and Applications

Control of a robot manipulator in contact with the environment is usually conducted by a direct feedback control system using a force–torque sensor or an indirect impedance control scheme. Although these methods have been successfully applied to many applications, simultaneous control of force and position cannot be achieved. To cope with such problems, this paper proposes a novel design of a dual actuator unit (DAU) composed of two actuators and a planetary gear train to provide the capability of simultaneous control of position and stiffness. Since one actuator controls position and the other actuator modulates stiffness, the DAU can control the position and stiffness simultaneously at the same joint. Both the torque exerted on the joint and the stiffness of the environment can be estimated without an expensive force sensor. Various experiments demonstrate that the DAU can provide good performance for position tracking, force estimation, and environment estimation.      

电流传感器在巡线机器人夹紧力测量中的应用

针对高压巡线机器人夹紧力测量的特殊要求,提出了一种通过测量电机的驱动电流间接获取夹紧力的方法,并从理论上验证了该方法的正确性。通过对实验数据的分析,提出了软件处理算法流程。实验结果表明,采用电流传感器测量巡线机器人夹紧力,反应灵敏、抗干扰能力强、安全可靠,成本低廉。该方法可应用于过载保护、拉压力控制等场合。     

"Sticky Hands": learning and generalization for cooperative physical interactions with a humanoid robot

"Sticky Hands" is a physical game for two people involving gentle contact with the hands. The aim is to develop relaxed and elegant motion together, achieve physical sensitivity-improving reactions, and experience an interaction at an intimate yet comfortable level for spiritual development and physical relaxation. We developed a control system for a humanoid robot allowing it to play Sticky Hands with a human partner. We present a real implementation including a physical system, robot control, and a motion learning algorithm based on a generalizable intelligent system capable itself of generalizing observed trajectories' translation, orientation, scale and velocity to new data, operating with scalable speed and storage efficiency bounds, and coping with contact trajectories that evolve over time. Our robot control is capable of physical cooperation in a force domain, using minimal sensor input. We analyze robot-human interaction and relate characteristics of our motion learning algorithm with recorded motion profiles. We discuss our results in the context of realistic motion generation and present a theoretical discussion of stylistic and affective motion generation based on, and motivating cross-disciplinary research in computer graphics, human motion production and motion perception.