Dealing with internal and external perturbations on walking robots

Up to now, walking robots have been working outdoors under favorable conditions and using very large stability margins to cope with natural environments and intrinsic robot dynamics that can cause instability in these machines when they use statically-stable gaits. The result has been very slow robots prone to tumble down in the presence of perturbations. This paper proposes a novel gait-adaptation method based on the maximization of the Normalized Dynamic Energy Stability Margin. This method enables walking-machine gaits to adapt to internal (robot dynamics) and external (environmental) perturbations, including the slope of the terrain, by finding the gait parameters that maximize robot stability. The adaptation method is inspired in the natural gait adaptation carried out by humans and animals to balance external forces or the effect of sloping terrain. Experiments with the SILO4 quadruped robot are presented and show how robot stability is more robust when the proposed approach is used for different external forces and sloping terrains. Using the proposed gait-adaptation approach the robot is able to withstand external forces up to 58% the robot weight and 25-degree slopes.

Stability analysis of position and force control for robot arms

Stability issues involving the control of a robot arm under the influence of external forces are discussed. Several different scenarios are considered: position control with the external force as an unmodeled disturbance, compliant control for a bounded external force in some subspace, and compliant control for a force due to the interaction with an environment whose dynamical behavior can be modeled. In each of these cases, a stability analysis using the Lyapunov method is presented. An explanation of instability is suggested in the case that the environment has flexibility and the gains are inappropriately chosen. When the environment is stiff in the force control subspace, robust (in time delay) stability can be achieved via the integral force feedback. However, the integral feedback gain should be chosen sufficiently small to account for possible flexibility in the system     

Stabilization of robot motion and contact force interaction for third-order motor dynamics

An approach to the synthesis of control laws stabilizing motion and force in contact tasks, based on the exponential stability of the closed-loop control system, is described. When using the synthesized control laws, simultaneous stabilization of both motion and force is achieved with a preset quality of the transient responses. The task is solved in a most general form, taking into account the constraints on robot control, its position and the force of interaction of the robot and the environment, and the external perturbations and inaccuracies of the measuring sensors, when the environment dynamics is being described by nonlinear second-order differential equation, and the robot dynamics includes the third-order equations of the robot actuators dynamics.     

侧向推搡下的四足机器人复合抗扰控制策略

针对四足机器人侧向推搡下的平衡恢复问题,提出了一种复合抗扰反应式鲁棒控制策略.该策略由摆动相的自适应侧摆规划策略和支撑相的关节抗扰控制构成.摆动相自适应侧摆规划策略通过四足机器人足端落地点的力平衡条件进行主动式步态规划以保证机器人在侧向推搡下的姿态稳定,并基于关节输出力矩给出了侧摆的启动条件.支撑相关节抗扰控制通过带扰动项的四足机器人完整动力学模型设计了基于干扰观测器的鲁棒滑模控制器,实现对侧向推搡扰动的补偿.最后,通过Matlab与ADAMS联合仿真验证了提出的控制策略的有效性.     

基于接触力信息的仿人机器人ZMP测量系统

针对现有仿人机器人零力矩点(ZMP)测量系统的力/力矩传感器不直接触地导致不能充分反映脚底各部位受力的问题,设计了一种基于地面接触力信息的具有传感器阵列的ZMP测量系统。介绍了传感器信号多级放大、采集及处理的软硬件系统,应用CAN总线接口实现了与外部上位机的通信。所设计的系统已应用于实际仿人机器人。步行实验表明:该系统能有效完成步行中ZMP的实时测量和脚底各部位受力信息的实时采集、计算与通信,简单易实现。     

Snake Robot Obstacle-Aided Locomotion: Modeling, Simulations, and Experiments

Snakes utilize irregularities in the terrain, such as rocks and vegetation, for faster and more efficient locomotion. This motivates the development of snake robots that actively use the terrain for locomotion, i.e., obstacle-aided locomotion. In order to accurately model and understand this phenomenon, this paper presents a novel nonsmooth (hybrid) mathematical model for wheel-less snake robots, which allows the snake robot to push against external obstacles apart from a flat ground. The framework of nonsmooth dynamics and convex analysis allows us to systematically and accurately incorporate both unilateral contact forces (from the obstacles) and isotropic friction forces based on Coulomb's law using set-valued force laws. The mathematical model is verified through experiments. In particular, a back-to-back comparison between numerical simulations and experimental results is presented. It is, furthermore, shown that the snake robot is able to move forward faster and more robustly by exploiting obstacles.     

Human Interaction Dynamics for Its Use in Mobile Robotics:Impedance Control for Leader-follower Formation

A complete characterization of the behavior in human-robot interactions (HRI) includes both:the behavioral dynamics and the control laws that characterize how the behavior is regulated with the perception data. In this way, this work proposes a leader-follower coordinate control based on an impedance control that allows to establish a dynamic relation between social forces and motion error. For this, a scheme is presented to identify the impedance based on fictitious social forces, which are described by distance-based potential fields. As part of the validation procedure, we present an experimental comparison to select the better of two different fictitious force structures. The criteria are determined by two qualities:least impedance errors during the validation procedure and least parameter variance during the recursive estimation procedure. Finally, with the best fictitious force and its identified impedance, an impedance control is designed for a mobile robot Pioneer 3AT, which is programmed to follow a human in a structured scenario. According to results, and under the hypothesis that moving like humans will be acceptable by humans, it is believed that the proposed control improves the social acceptance of the robot for this kind of interaction.      

基于Netvlad神经网络的变磁力吸附爬壁机器人控制系统设计

变磁力吸附爬壁机器人是一种具有快速、灵活移动方式的爬行机器人,但其吸附力难以控制,越障稳定性较差,难以保证机器人的平稳爬行;为实现爬壁机器人在大型建筑结构外表面的自主避障,提升机器人与运动平面之间的吸附紧密性,设计基于Netvlad神经网络的变磁力吸附爬壁机器人控制系统;按照PCB控制要求,连接外置SRAM设备与传感器模块,借助驱动I/O口电路提供的电力驱动作用,控制气动阀门的闭合情况,完成变磁力吸附爬壁机器人控制系统硬件结构设计;建立Netvlad神经网络体系,通过划分控制指令程序任务的方式,确定移植参数取值范围,实现对控制协议的移植处理,联合相关硬件应用结构,完成基于Netvlad神经网络的变磁力吸附爬壁机器人控制系统设计;实验结果表明,在所设计系统作用下,障碍物所在位置与爬壁机器人所在位置之间的实测距离未大于30cm,能够有效实现自主避障,保证机器人与运动平面之间的紧密吸附。     

An adaptive control strategy for postural stability using a wearable robot

Wearable robots are expected to expand the use of robotics in rehabilitation since they can widen the assistance application context. An important aspect of a rehabilitation therapy, in terms of lower extremity assistance, is balance control. In this article, we propose and evaluate an adaptive control strategy for robotic rehabilitation therapies to guarantee static stability using a wearable robot. Postural balance control can be implemented either acting on the hip, on the ankle joint or on both, depending on the kind of perturbation acting on the subject: internal or external. Internal perturbations can be produced by any voluntary movement of the body, such as bending the trunk. External perturbations, in the form of an impact force, are applied by the exoskeleton without any prior notice to observe the proactive response of the subject. We have used a 6 degree of freedom planar lower limb exoskeleton, H1, to perform this analysis. The developed control strategy has been designed to provide the necessary assistance, related to balance recovery and postural stability, under the “Assist-as-needed” paradigm. The interaction forces between orthosis and subject are monitored, as they play a relevant role in the definition of assistive and resistive movements to be applied to the joints. The proposed method has been tested with 5 healthy subjects in presence of internal and external disturbances. The results demonstrate that knowing the stability limit of each subject, in combination with a therapeutically selected scaling factor, the proposed adaptive control helps in providing an effective assistance in therapy. This method is efficient in handling the individual and combined effect of external perturbations acting on any joint movements.     

Compliant Terrain Adaptation for Biped Humanoids Without Measuring Ground Surface and Contact Forces

This paper reports the applicability of our passivity-based contact force control framework for biped humanoids. We experimentally demonstrate its adaptation to unknown rough terrain. Adaptation to uneven ground is achieved by optimally distributed antigravitational forces applied to preset contact points in a feedforward manner, even without explicitly measuring the external forces or the terrain shape. Adaptation to unknown inclination is also possible by combining an active balancing controller based on the center-of-mass (CoM) measurements with respect to the inertial frame. Furthermore, we show that a simple impedance controller for supporting the feet or hands allows the robot to adapt to low-friction ground without prior knowledge of the ground friction. This presentation includes supplementary experimental videos that show a full-sized biped humanoid robot balancing on uneven ground or time-varying inclination.      

基于测力平台阵列的双足步行机器人实际零力矩点检测

提出一种多维力测力平台阵列系统,通过机器人行走过程中脚部与平台接触力的测量,并根据. vukobratovic关于ZMP的定义,得到机器人行走过程的ZMP实际轨迹信息,为双足步行机器人的稳态行走步态规划提 供参考依据.更进一步,该系统也可以用作双足步行机器人行走过程步态规划的实验平台.     

Quadruped robot trotting over irregular terrain assisted by stereo-vision

Legged robots have the potential to navigate in challenging terrain, and thus to exceed the mobility of wheeled vehicles. However, their control is more difficult as legged robots need to deal with foothold computation, leg trajectories and posture control in order to achieve successful navigation. In this paper, we present a new framework for the hydraulic quadruped robot HyQ, which performs goal-oriented navigation on unknown rough terrain using inertial measurement data and stereo-vision. This work uses our previously presented reactive controller framework with balancing control and extends it with visual feedback to enable closed-loop gait adjustment. On one hand, the camera images are used to keep the robot walking towards a visual target by correcting its heading angle if the robot deviates from it. On the other hand, the stereo camera is used to estimate the size of the obstacles on the ground plane and thus the terrain roughness. The locomotion controller then adjusts the step height and the velocity according to the size of the obstacles. This results in a robust and autonomous goal-oriented navigation over difficult terrain while subject to disturbances from the ground irregularities or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness of this framework.     

Near Optimal Robust Path Planning for Mobile Robots: the Viscous Fluid Method with Friction

A new approach is proposed to robot path planning that consists of using the viscous fluid equations including external forces. Unlike the majority of potential field techniques, the method is able to cope not only with 2-dimensional binary environments made of obstacles and free space, but also with so-called weighted regions, as well as uneven natural terrain where slope and ground characteristics influence the robot performance. It shows how the viscosity coefficient can be used to control the corridors of navigation, and how the external forces acting on the fluid particles can model the forces due to gravity and to friction between the ground and the vehicle. The planner automatically constructs several routes of equivalent costs, that makes the solutions more robust than those obtained by the search of optimal paths, by allowing reactivity in case of an unexpected local disturbance. Comparisons with the scent diffusion method for a binary universe and with a genetic algorithm for a real natural terrain are presented.     

Generation of a continuous free gait for quadruped robot over rough terrains

Generating a robust gait is one of the most important factors to improve the adaptability of quadruped robots on rough terrains. This paper presents a new continuous free gait generation method for quadruped robots capable of walking on the rough terrain characterized by the uneven ground and forbidden areas. When walking with the proposed gait, the robot can effectively maintain its stability by using the Center of Gravity (COG) trajectory planning method. After analyzing the point cloud of rough terrain, the forbidden areas of the terrain can be obtained. Based on this analysis, an optimal foothold search strategy is presented to help quadruped robot to determine the optimum foothold for the swing foot automatically. In addition, the foot sequence determining method is proposed to improve the performance of robot. With the free gait proposed in this paper, quadruped robot can walk through the rough terrains automatically and successfully. The correctness and effectiveness of the proposed method is verified via simulations.     

Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces

This paper proposes an effective framework of human-humanoid robot physical interaction. Its key component is a new control technique for full-body balancing in the presence of external forces, which is presented and then validated empirically. We have adopted an integrated system approach to develop humanoid robots. Herein, we describe the importance of replicating human-like capabilities and responses during human-robot interaction in this context. Our balancing controller provides gravity compensation, making the robot passive and thereby facilitating safe physical interactions. The method operates by setting an appropriate ground reaction force and transforming these forces into full-body joint torques. It handles an arbitrary number of force interaction points on the robot. It does not require force measurement at interested contact points. It requires neither inverse kinematics nor inverse dynamics. It can adapt to uneven ground surfaces. It operates as a force control process, and can therefore, accommodate simultaneous control processes using force-, velocity-, or position-based control. Forces are distributed over supporting contact points in an optimal manner. Joint redundancy is resolved by damping injection in the context of passivity. We present various force interaction experiments using our full-sized bipedal humanoid platform, including compliant balance, even when affected by unknown external forces, which demonstrates the effectiveness of the method.     

Optimal impedance control based on body inertia for a hydraulically driven hexapod robot walking on uneven and extremely soft terrain

This paper presents the implementation of impedance control for a hydraulically driven hexapod robot named COMET‐IV, which can walk on uneven and extremely soft terrain. To achieve the dynamic behavior of the hexapod robot, changes in center of mass and body attitude must be taken into consideration during the walking periods. Indirect force control via impedance control is used to address these issues. Two different impedance control schemes are developed and implemented: single‐leg impedance control and center of mass‐‐based impedance control. In the case of single‐leg impedance control, we derive the necessary impedance and adjust parameters (mass, damping, and stiffness) according to the robot legs' configuration. For center of mass–based impedance control, we use the sum of the forces of the support legs as a control input (represented by the body's current center of mass) for the derived impedance control and adjust parameters based on the robot body's configuration. The virtual forces from the robot body's moment of inertia are adapted to achieve optimal control via a linear quadratic regulator method for the proposed indirect attitude control. In addition, a compliant switching mechanism is designed to ensure that the implementation of the controller is applicable to the tripod sequences of force‐based walking modules. Evaluation and verification tests were conducted in the laboratory and the actual field with uneven terrain and extremely soft surfaces. © 2011 Wiley Periodicals, Inc.     

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.     

Translational Crawl and Path Tracking of a Quadruped Robot

Translational crawl and path tracking are presented for a quadruped robot, named TITAN‐VIII, to walk on rough ground. The generalized and explicit formulation is derived to generate the translational crawl gait in an arbitrary direction automatically, to control the joint positions, and to estimate the robot localization in a walking environment. Compared to conventional gaits, the proposed gait is characterized by a natural and continuous transition between any successive gait cycles, by a maximized stride of the robot in each gait cycle, and by different foot trajectories corresponding to the uneven terrain. Especially, the proposed approach enables the quadruped robot to track a reference path in a complex walking environment, based on dead‐reckoning localization for the robot. The effectiveness of the proposed method is demonstrated through the experimental results. © 2002 Wiley Periodicals, Inc.     

Dynamic postural control method for biped in unknown environment

We propose a new way to solve the dynamic equilibrium problem of a biped robot under unknown external perturbations. For that, a multichain mechanical model of a human body (called BIPMAN) is proposed with a general architecture. The principle of the dynamic postural control is based on the correction of the trunk center of mass acceleration and on the force distribution exerted by the limbs on the trunk. To ensure a real time dynamic compensation faced to an unknown external perturbation, we have introduced a new approach called real time criteria and constraints adaptation. This is based on a linear programming technique with a general criterion which optimizes the force distribution. The ponderation coefficients and the task constraints notions are introduced in order to specify criteria and constraints adapted to specific task classes in presence of an unknown external perturbation. Many results are presented to demonstrate criteria and constraints influences on the dynamic equilibrium