变长度弹性伸缩腿双足机器人半被动起步行走仿人控制

传统双足机器人行走使用轨迹跟踪控制,而人类行走大部分时间处于被动状态.针对半被动变长度弹性伸缩腿双足机器人从静止状态开始起步行走的问题,提出了一种起步行走仿人控制方法.首先,使用串联弹性驱动双足弹簧负载倒立摆(B-SLIP)模型;然后,利用拉格朗日方法建立行走动力学方程,并利用模型的自稳定性在双支撑阶段采用能量误差比例...     

伸缩腿双足机器人半被动行走控制研究

研究半被动伸缩腿双足机器人行走控制和周期解的全局稳定性问题.使用杆长可变的倒立摆机器人模型,以支撑腿的伸缩作为行走动力源,采用庞加莱映射方法分析了双足机器人行走的不动点及其稳定性.当脚与地面冲击时,假设两腿间的夹角保持为常数,设计了腿伸缩长度的支撑腿角度反馈控制率.证明了伸缩腿双足机器人行走过程不动点的全局稳定性.仿真结果表明,本文提出的腿伸缩长度反馈控制可以实现伸缩腿双足机器人在水平面上的稳定行走,并且周期步态对执行器干扰和支撑腿初始角速度干扰具有鲁棒性.     

Trajectory generation and control for a biped robot walking upstairs

This paper presents an effective and systematic trajectory generation method, together with a control method for enabling a biped robot to walk upstairs. The COG (center of gravity) trajectory is generated by the VHIPM (virtual height inverted pendulum mode) for the horizontal motion and by a 6th order polynomial for the vertical motion; an ankle compliance control (ACC) is also added into the robot control. The proposed methods are evaluated by simulations as well as being implemented in a robot for the performance verification. The results show that the proposed methods can generate stable motions when walking upstairs, and these can significantly reduce the zero moment point (ZMP) errors compared with other methods, enabling the robot to walk up steeper stairs.     

Development of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems

This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decoupling the walking motion control from the sideway balancing control.This strategy allows the walking controller to execute the walking task independently while the sideway balancing controller continuously maintains the balance of the robot.The hip-mass carry approach and selected stages of walk implemented in the control strategy can minimize the efect of major hip mass of the robot on the stability of its walk.In addition,the developed smooth joint trajectory planning eliminates the impacts of feet during the landing.In this paper,the new design of mechanism for locomotion systems and balancing systems are introduced.An additional degree of freedom introduced at the ankle joint increases the sensitivity of the system and response time to the sideway disturbances.The efectiveness of the proposed strategy is experimentally tested on a bipedal robot prototype.The experimental results provide evidence that the proposed strategy is feasible and advantageous.     

Adaptive walking control of quadruped robots based on central pattern generator （CPG） and reflex

This paper presents a central pattern generator (CPG) and vestibular reflex combined control strategy for a quadruped robot. An oscillator network and a knee-to-hip mapping function are presented to realize the rhythmic motion for the quadruped robot. A two-phase parameter tuning method is designed to adjust the parameters of oscillator network. First, based on the numerical simulation, the influences of the parameters on the output signals are analyzed, then the genetic algorithm (GA) is used to evolve the phase relationships of the oscillators to realize the basic animal-like walking pattern. Moreover, the animal’s vestibular reflex mechanism is mimicked to realize the adaptive walking of the quadruped robot on a slope terrain. Coupled with the sensory feedback information, the robot can walk up and down the slope smoothly. The presented bio-inspired control method is validated through simulations and experiments with AIBO. Under the control of the presented CPG and vestibular reflex combined control method, AIBO can cope with slipping, falling down and walk on a slope successfully, which demonstrates the effectiveness of the proposed walking control method.     

Experimental realization of dynamic walking for a human-riding biped robot,HUBO FX-1

This paper describes a control strategy of the stable walking for the human-riding biped robot, HUBO FX-1. HUBO FX-1 largely consists of two legs with 12 d.o.f., a pelvis and a cockpit. A normal adult can easily ride on HUBO FX-1 by means of a foothold, and can change the walking direction and speed continuously through the use of a joystick. Principally, this kind of robot must be able to carry a payload of at least 100 kg in order to carry a person easily. A sufficient payload can be accomplished by two ways. The first is through the choice of a highly efficient actuator. The second is through weight reduction of the robot body frames. As an efficient actuator, a high-power AC servo motor and a backlash-free harmonic drive reduction gear were utilized. Furthermore, the thickness and the size of the aluminum body frames were sufficiently reduced so that the weight of HUBO FX-1 is light enough. The disadvantage of the weight reduction is that HUBO FX-1 was not able to walk stably due to structural vibrations, as the body structures become more flexible due to this procedure. This problem was solved through the use of a simple theoretical model and a vibration reduction controller based on sensory feedback. In order to endow the robot with a stable biped walking capability, a standard walking pattern and online controllers based on the real-time sensory feedback were designed. Finally, the performance of the real-time balance control strategy was experimentally verified and stable dynamic walking of the human-riding biped robot, HUBO FX-1, carrying one passenger was realized.     

Adaptive Gait Control of a Biped Robot Based on Realtime Sensing of the Ground Profile

In this paper, realtime control of dynamic biped locomotion usingsensor information is investigated. We used an ultrasonic rangesensor mounted on the robot to measure the distance from the robot tothe ground surface. During the walking control, the sensor data isconverted into a simple representation of the ground profile inrealtime. We also developed a control architecture based on theLinear Inverted Pendulum Mode which we proposed previously fordynamic walking control. Combining the sensory system and thecontrol system enabled our biped robot, Meltran II, to walk overground of unknown profile successfully.     

Study of lower level adaptive walking in the sagittal plane by a biped locomotion robot

Walking according to changes in the environment is called adaptive walking. We define lower level adaptive walking as a walk consisting only of trajectory control and walk-pattern generation. The purpose of this study was to realize lower level adapting walking in the sagittal plane by a biped locomotion robot in indoor space. In this paper, we propose a simplified procedure of walk-pattern generation, which is that walk patterns for various environments are generated by adjusting and combining the basic walk patterns which have previously been given for typical environments. Based on this idea, walking experiments were carried out for various environments. As a result, dynamic walking in a flat plane (about 1.5 s/step with a 0.3 m step width), changes of the step width in walking, and walking in various environments combined from a flat plane, an obstacle (such as a pipe) and a stair (up and down) were realized.     

A reflexive neural network for dynamic biped walking control

Biped walking remains a difficult problem, and robot models can greatly facilitate our understanding of the underlying biomechanical principles as well as their neuronal control. The goal of this study is to specifically demonstrate that stable biped walking can be achieved by combining the physical properties of the walking robot with a small, reflex-based neuronal network governed mainly by local sensor signals. Building on earlier work (Taga, 1995; Cruse, Kindermann, Schumm, Dean, & Schmitz, 1998), this study shows that human-like gaits emerge without specific position or trajectory control and that the walker is able to compensate small disturbances through its own dynamical properties. The reflexive controller used here has the following characteristics, which are different from earlier approaches: (1) Control is mainly local. Hence, it uses only two signals (anterior extreme angle and ground contact), which operate at the interjoint level. All other signals operate only at single joints. (2) Neither position control nor trajectory tracking control is used. Instead, the approximate nature of the local reflexes on each joint allows the robot mechanics itself (e.g., its passive dynamics) to contribute substantially to the overall gait trajectory computation. (3) The motor control scheme used in the local reflexes of our robot is more straightforward and has more biological plausibility than that of other robots, because the outputs of the motor neurons in our reflexive controller are directly driving the motors of the joints rather than working as references for position or velocity control. As a consequence, the neural controller and the robot mechanics are closely coupled as a neuromechanical system, and this study emphasizes that dynamically stable biped walking gaits emerge from the coupling between neural computation and physical computation. This is demonstrated by different walking experiments using a real robot as well as by a Poincaré map analysis applied on a model of the robot in order to assess its stability.     

Development of an artificial muscle linear actuator using ionic polymer–metal composites

We are developing an artificial muscle linear actuator using ionic polymer-metal composites (IPMC)—electro-active polymers that bend in response to electric stimuli—and the goal of our study is applying the actuator to robotic applications, especially to a biped walking robot. In this paper, we will describe the structure of the actuator and an empirical model of the actuator which has two inputs and one output, and whose parameters are identified from input-output data. Based on the empirical model, basic experiments and position control of the linear actuator are demonstrated. Then, we consider walking control of a small-sized biped walking robot. In the application we assume that the developed actuators are connected both in series and in parallel to a joint of the walking robot so that the actuators supply enough torque to the robot, and that they are stretched and compressed enough. It is shown throughout simulations that the biped walking robot with the actuators can walk on level ground with a period synchronized with the period of the input signal.     

A desired landing points walking method enablinga planner quadruped robot to walk on rough terrain

It is necessary for legged robots to walk stably and smoothly on rough terrain.In this paper,a desired landing points(DLP) walking method based on preview control was proposed in which an off-line foot motion trace and an on-line modification of the trace were used to enable the robot to walk on rough terrain.The on-line modification was composed of speed modification,foot lifting-off height modification,step length modification,and identification and avoidance of unsuitable landing terrain.A planner quadruped robot simulator was used to apply the DLP walking method.The correctness of the method was proven by a series of simulations using the Adams and Simulink.     

Analyses of biped walking posture by dynamical-evaluating index

In this paper, biped walking posture and design are evaluated through dynamic reconfiguration manipulability shape index (DRMSI). DRMSI is the concept derived from dynamic manipulability and reconfiguration manipulability with remaining redundancy. DRMSI represents the ability of dynamical system of manipulators possessing shape changing acceleration in task space by normalized torque inputs, while the hand motion is assigned as the primary task. Besides, we use visual lifting approach to stabilize the walking and stop falling down. In this research, the primary task is to make the position of the head direct to the desired one as much as possible. And realizing the biped walking is the second task. This research indicates that proposed dynamical-evaluating index is effective in evaluating the biped walking motion and biped humanoid robot has the adjustable configuration to walk with higher flexibility. Flexibility represents the dynamical shape changeability of humanoid robot based on redundancy of the humanoid robot with the premise of the primary task given to keeping the head position high.     

Quadruped walking robots at Tokyo Institute of Technology

I(Hirose) was walking along a mountain path near Mt. Fuji on a summer day of 1976, when I found a daddy long-legs walking on the ground. I picked it up in my palm and allowed it to walk over my fingers, and the bug walked effortlessly even over finger-made obstacles ten times larger than its own body. While I was watching the motion of the bug, I started to have the desire to make bigger multilegged walking robots, which can walk over large buildings. This was the beginning of our study of walking robots, which was to last for more than 30 years.     

Bipedal robot walking control on inclined planes by fuzzy reference trajectory modification

The two-legged humanoid structure has advantages for an assistive robot in the human living and working environment. However, the control of bipedal walk is a challenge. Walking performance on solely even floor is not satisfactory. This paper presents a study on bipedal walk on inclined planes with changing slopes. A Zero Moment Point (ZMP) based gait synthesis technique is employed. The pitch angle reference for the foot sole plane—as expressed in a coordinate frame attached at the robot body—is adjusted online by a fuzzy logic system to adapt to different walking surface slopes. Ankle pitch torques and the average value of the body pitch angle, computed over a history of a predetermined number of sampling instants, are used as the inputs to this system. The proposed control method is tested via walking experiments with the 29 degrees-of-freedom human-sized full-body humanoid robot SURALP (Sabanci University Robotics Research Laboratory Platform) on even floor and inclined planes with different slopes. The results indicate that the approach presented is successful in enabling the robot to stably enter, ascend and leave inclined planes with 15?% (8.5°) grade. This, to the best knowledge of the authors, constitutes the steepest ascend reported to date, with a transition from even floor, by a blind walking biped robot.     

复杂环境下仿人机器人有效支撑区域的感知

当主流的仿人机器人都采ZMP(zero moment point)理论作为稳定行走的判据.实时ZMP点落在支撑足与地面接触形成的多边形支撑区域内是仿人机器人实现稳定步行的必要条件.因此实现仿人机器人在复杂现实环境中稳定行走,必须要求机器人足部感知系统提供足够丰富的地面环境信息,从而可以准确获取支撑区域的形状以实现基于实时ZMP点的稳定控制.文中将柔性阵列力传感器应用于仿人机器人足部感知系统,提出了获取仿人机器人支撑区域形状的方法,而且通过实验验证了其可行性.     

Passively walking five-link robot

In this article we investigate the dynamics of a five-link, passive bipedal robot. The passivity in this context stands for the ability of the robot to walk autonomously down an inclined surface without any external source of energy. Previous research efforts in passive walking were limited to four link models with knees or 2-link models without knees with a variety of mass distributions. In this paper we analyze the dynamics of a five-link robot with knees and upper body. We were successful in detecting three limit cycles that include three distinct upper body motions. We have investigated the structural stability of these cycles subject to variations in the upper body length. The results demonstrated that the stability can be improved with addition of linear dampers in the hip joints of the model. Also, our investigation demonstrated that erect body posture is only achievable when torsional springs are placed in the hip joints.     

Neuromechanical control for hexapedal robot walking on challenging surfaces and surface classification

The neuromechanical control principles of animal locomotion provide good insights for the development of bio-inspired legged robots for walking on challenging surfaces. Based on such principles, we developed a neuromechanical controller consisting of a modular neural network (MNN) and of virtual agonist–antagonist muscle mechanisms (VAAMs). The controller allows for variable compliant leg motions of a hexapod robot, thereby leading to energy-efficient walking on different surfaces. Without any passive mechanisms or torque and position feedback at each joint, the variable compliant leg motions are achieved by only changing the stiffness parameters of the VAAMs. In addition, six surfaces can be also classified by observing the motor signals generated by the controller. The performance of the controller is tested on a physical hexapod robot. Experimental results show that it can effectively walk on six different surfaces with the specific resistances between 9.1 and 25.0, and also classify them with high accuracy.     

Design of six-legged walking robot,Little Crabster for underwater walking and operation

This paper describes the development of a ground test robot platform to study a multi-legged walking robot capable of precise proximity exploration and operations under a shallow sea in the presence of a strong tidal current environment. For both underwater walking and complex operations, a six-legged robot that uses two legs as manipulators during underwater operations is proposed. The dimensions, joint structure, range of motion, and mass distribution of the robot are determined by considering biological data, and then suitable joint actuators are chosen through a simple force analysis. In addition, a main controller, a communication bus, motor controllers, sensors, and a battery are chosen to build the whole control system. The detailed design is performed using 2D/3D computer aided design (CAD) software, and the robot is finally built by machining the parts and assembling them. The degree of design completion is proved by basic walking experiments and future works are addressed.     

A dung beetle-inspired robotic model and its distributed sensor-driven control for walking and ball rolling

A typical approach when designing a bio-inspired robot is to simplify an animal model and to enhance the functionality of interest. For hexapod robots, this often leads to a need of supplementary mechanics to become multifunctional. However, a preferable solution is to employ the embodied multifunctional capabilities of the animal as inspiration for robot design. Using this approach, we present a method for translating the kinematic chain of a dung beetle from which an accurate kinematic model and a simplified one were simulated and compared. The beetle was selected due to its multifunctional locomotory capabilities including walking as well as standing on and rolling a ball. For testing the models, we developed a distributed sensor-driven controller that can generate walking and ball-rolling behaviors. A comparison of the two modeling approaches shows a similar performance with regards to walking stability and accuracy, but differences when it comes to speed and multifunctionality. This is because the accurate model is able to use its legs to walk faster and roll a ball, which the simplified one is not. In conclusion, the accurate model of a dung beetle-inspired robot is advantageous as it, together with our novel control mechanism, is able to elicit behaviors comparable to those of the real dung beetle (i.e., walking and rolling a dung ball).     

Intention-based walking support for paraplegia patients with Robot Suit HAL

This paper proposes an algorithm to estimate human intentions related to walking in order to comfortably and safely support a paraplegia patient's walk. Robot Suit HAL (Hybrid Assistive Limb) has been developed for enhancement of a healthy person's activities and for support of a physically challenged person's daily life. The assisting method based on bioelectrical signals such as myoelectricity successfully supports a healthy person's walking. These bioelectrical signals, however, cannot be measured properly from a paraplegia patient. Therefore another interface that can estimate a patient's intentions without any manual controller is desired for robot control since a manual controller deprives a patient of his/her hand freedom. Estimation of a patient's intentions contributes to providing not only comfortable support but also safe support, because any inconformity between the robot suit motion and the patient motion results in his/her stumbling or falling. The proposed algorithm estimates a patient's intentions from a floor reaction force (FRF) reflecting a patient's weight shift during walking and standing. The effectiveness of this algorithm is investigated through experiments on a paraplegia patient who has a sensory paralysis on both legs, especially his left leg. We show that HAL supports the patient's walk properly, estimating his intentions based on the FRF, while he keeps his own balance by himself.