Reflex control of bipedal locomotion on a slippery surface

Biped robots are expected to walk on many different and previously unknown terrains including slippery surfaces on which no prior information is available. It is very important that biped robots have an ability to walk on a slippery surface which it meets so suddenly, since any damage to biped robots will be very costly. In order to prevent falling down on a suddenly encountered slippery surface, this paper proposes a reflex control method for biped robots to quickly recover their posture from a foot slip upon its detection. Computer simulations were performed with a 12-d.o.f. biped robot model and a 6-d.o.f. elastic pad model, the latter of which consists of nonlinear dampers, and linear and nonlinear springs. Simulation results show that the proposed method is very effective in preventing biped robots falling down when walking on a slippery surface.     

Simultaneous bipedal locomotion based on haptics for teleoperation

ABSTRACT

This paper proposes a novel, simultaneous bipedal locomotion method using haptics for remote operation of biped robots. In general, traditional biped walking methods require very high computational power and advanced controllers to perform the required task. However, in this proposed method, a master exoskeleton attached to the human’s lower body is used to obtain the trajectory and haptic information to generate the trajectory of the slave biped robot in real time. Lateral motion of the center of mass of the biped is constrained in this experiment. Also, it is considered that no communication delay is presented in between the two systems in this experiment, and they are not discussed in this paper. Since a direct motion transmission is used in the proposed method, this method is quite straight forward and a simultaneous walking can be realized at the same time with high performance. Also, it does not require an exact dynamic model of the biped or specific method to plan the trajectory. The gait pattern of the biped is directly determined by that of the human. Also, the operator can feel the remote environment through the exoskeleton robot. Results obtained from the experiments validate the proposed method.     

Hybrid-state driven autonomous control for planar bipedal locomotion

The focus of this paper is on the development of a human inspired autonomous control scheme for a planar bipedal robot in a hybrid dynamical framework to realize human-like walking projected onto sagittal plane. In addition, a unified modelling scheme is presented for the biped dynamics incorporating the effects of various locomotion constraints due to varying feet-ground contact states, unilateral ground contact force, contact friction cone, passive dynamics associated with floating base etc. along with a practical impact velocity map on heel strike event. The autonomous control synthesis is formulated as a two-level hierarchical control algorithm with a hybrid-state based supervisory control in outer level and an integrated set of constrained motion control primitives, called task level control, in inner level. The supervisory level control is designed based on a human inspired heuristic approach whereas the task level control is formulated as a quadratic optimization problem with linear constraints. The explicit analytic solution obtained in terms of joint acceleration and ground contact force is used in turn to generate the joint torque command based on inverse dynamics model of the biped. The proposed controller framework is named as Hybrid-state Driven Autonomous Control (HyDAC). Unlike many other bipedal control schemes, HyDAC does not require a preplanned trajectory or orbit in terms of joint variables for locomotion control. Moreover, it is built upon a set of basic motion control primitives similar to those in human walk which provides a transparent and easily adaptable structure for the controller. These features make HyDAC framework suitable for bipedal walk on terrain with step and slope discontinuities without a priori gait optimization. The stability and agility of the proposed control scheme are demonstrated through dynamic model simulation of a 12-link planar biped having similar size and mass properties of an adult sized human being restricted to sagittal plane. Simulation results show that the planar biped is able to walk for a speed range of 0.1–2 m/s on level terrain and for a ground slope range of $+/-$20 deg for 1 m/s speed.     

Component based computational model for bipedal locomotion

Bipedal locomotion has been an active area of research for many decades, it has wide ranging applications in the field of humanoid locomotion, as well as in the understanding of the biomechanics of normal human gait. Inherently human gait is a complex non-linear dynamic system, which is usually modeled by a set of differential equations satisfying a given set of constraints. In this paper an attempt has been made to view gait from the perspective of software engineering. In doing so, the entire gait cycle has been discretized into phases and sub-phases and modeled using a hybrid automaton, subsequently the automaton has been integrated with the BIP(Behavior, Interaction, Priority) framework, thereby creating a component based computational framework for modeling biped locomotion. The correctness of the developed model has been validated and verified through simulation runs in OpenSim.     

Stabilization of bipedal walking based on compliance control

The embodiment of physical compliance in humanoid robots, inspired by biology, improves the robustness of locomotion in unknown environments. The mechanical implementation using elastic materials demands a further combination together with controlled compliance to make the intrinsic compliance more effective. We hereby present an active compliance control to stabilize the humanoid robots for standing and walking tasks. Our actively controlled compliance is achieved via admittance control using closed-loop feedback of the six axis force/torque sensors in the feet. The modeling and theoretical formulation are presented, followed by the simulation study. Further, the control algorithms were validated on a real humanoid robot COMAN with inherent compliance. A series of experimental comparisons were studied, including standing balancing against impacts, straight walking, and omni-directional walking, to demonstrate the necessity and the effectiveness of applying controlled compliance on the basis of physical elasticity to enhance compliant foot-ground interaction for the successful locomotion. All data from simulations and experiments related with the proposed controller and the performance are presented, analyzed, and discussed.     

Evolutionary control of bipedal locomotion in a high degree-of-freedom humanoid robot: first steps

This article describes a methodology, together with an associated series of experiments employing this methodology, for the evolution of walking behavior in a simulated humanoid robot with up to 20 degrees of freedom. The robots evolved in this study learn to walk smoothly in an upright or near-upright position and demonstrate a variety of different locomotive behaviors, including “skating,” “limping,” and walking in a manner curiously reminiscent of a mildly or heavily intoxicated person. A previous study demonstrated the possible potential utility of this approach while evolving controllers based on simulated humanoid robots with a restricted range of movements. Although walking behaviors were developed, these were slow and relied on the robot walking in an excessively stooped position, similar to the gait of an infirm elderly person. This article extends the previous work to a robot with many degrees of freedom, up to 20 in total (arms, elbows, legs, hips, knees, etc.), and demonstrates the automatic evolution of fully upright bipedal locomotion in a humanoid robot using an accurate physics simulator. This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

Mechanics of bipedal and quadrupedal locomotion on dry and wet granular media

The effectiveness of exploration robots is contingent upon their capability and efficiency to locomote on contorted and multifaceted terrains. Traditional wheeled robots do not suffice at overcoming such terrains and complications they introduce. The proposed work explores the performance of WhegRunner, a whegged (i.e., wheel-legged) robotic platform used to examine the mechanics of running on granular media at different saturation levels. In particular, the effect of bipedal/quadrupedal gait, saturation level, stride length, and stride frequency on robot's forward body velocity and cost of transport (COT) was studied. To increment nominal stride length, the robot was fitted with different number of spoked whegs from 3 to 7. In addition, eight evenly spaced motor speeds ranging from 2.33 to 7.43 Hz were used to observe the effect of stride frequency. Similar trends were observed between the two gaits, with the quadrupedal gait showing better overall performance. On dry sand, wider strides were attained at reduced motor speeds with lower spoked whegs. However, on wet sand (15% and 30% saturation), wider strides were achieved with higher motor speeds and lower spoked whegs. As a result, lower spoked whegs accomplished higher body forward velocity and lower COT as saturation increased. The acquired knowledge elucidates underexplored mechanics of locomotion on granular media at different saturation levels. The WhegRunner can be used as a platform to obtain a greater insight on how to develop more proficient exploration robots, ones which can face complex and deformable terrains and mediums.     

Graphical passwords based on robust discretization

This paper generalizes Blonder's graphical passwords to arbitrary images and solves a robustness problem that this generalization entails. The password consists of user-chosen click points in a displayed image. In order to store passwords in cryptographically hashed form, we need to prevent small uncertainties in the click points from having any effect on the password. We achieve this by introducing a robust discretization, based on multigrid discretization.     

连续属性的频数监督断点离散化技术

提出了一种频数监督断点的离散化算法。该算法利用所提出的频数监督断点思想产生初始断点,并在此基础上进行断点简约。实验结果表明该算法所产生的断点不仅符合实际数据分布,而且更为合理、精练。     

Hybrid disturbance rejection control of dynamic bipedal robots

This paper presents a disturbance rejection control strategy for hybrid dynamic systems exposed to model uncertainties and external disturbances. The focus of this work is the gait control of dynamic bipedal robots. The proposed control strategy integrates continuous and discrete control actions. The continuous control action uses a novel model-based active disturbance rejection control (ADRC) approach to track gait trajectory references. The discrete control action resets the gait trajectory references after the impact produced by the robot’s support-leg exchange to maintain a zero tracking error. A Poincaré return map is used to search asymptotic stable periodic orbits in an extended hybrid zero dynamics (EHZD). The EHZD reflects a lower-dimensional representation of the full hybrid dynamics with uncertainties and disturbances. A physical bipedal robot testbed, referred to as Saurian, is fabricated for validation purposes. Numerical simulation and physical experiments show the robustness of the proposed control strategy against external disturbances and model uncertainties that affect both the swing motion phase and the support-leg exchange.

     

Boundary element method based on preliminary discretization

A new numerical method for solving wave diffraction problems is given. The method is based on the concept of boundary elements; i.e., the unknown values are the field values on the surface of the scatterer. An analog of a boundary element method rather than a numerical approximation of the initial (continuous) problem is constructed for an approximate statement of the problem on the discrete lattice. Although it reduces the accuracy of the method, it helps to simplify the implementation significantly since the Green functions of the problem are no longer singular. In order to ensure the solution to the diffraction problem is unique (i.e., to suppress fictitious resonances), a new method is constructed similarly to the CFIE approach developed for the classical boundary element method.     

Non-linear observer based on the Euler discretization

In this paper we present an estimator based on the Euler discretization. First, we show that the proposed estimator is an exponential observer in the case when the error between trajectories of continuous time and its associated Euler discretized system can be neglected. Otherwise, we show that the error of estimation is exponentially attracted by some neighbourhood of the origin which depends only on the sampling time. Finally, numerical simulations using a bioreactor model are given in order to highlight the performance of the proposed estimator.     

基于多分辨离散模型的图形密码

为了增强点击型图形密码在触摸屏移动智能终端应用中的易用性和安全性,离散化过程中引入多分辨思想,提出了一种用于图形密码的多分辨离散模型。对比分析数据表明,多分辨离散模型可以在相同的图像尺寸和容错距离情况下,获得比已有离散化方法更大的密码空间,增加攻击难度,提高安全性。同时多分辨离散模型可调整安全强度,可通过扩大容错距离来提高易用性。     

基于集成学习的无监督离散化算法

模式识别与机器学习的一些算法只能处理离散属性值,而在现实生活中的很多数据具有连续的属性值,针对数据离散化的问题提出了一种无监督的方法。首先,使用K-means方法将数据集进行划分得到类别信息;然后,应用有监督的离散化方法对划分后的数据离散化,重复上述过程以得到多个离散化的结果,再将这些结果进行集成;最后,将集成得到的最小子区间进行合并,这里根据数据间的邻居关系选择优先合并的维度及相邻区间。其中,通过数据间的近邻关系自动寻求子区间数目,尽可能保持其内在结构关系不变。将离散后的数据应用于聚类算法,如谱聚类算法,并对聚类后的效果进行评价。实验结果表明,该算法聚类精确度比其他4种方法平均提高约33%,表明了该算法的可行性和有效性。通过该算法得到的离散化数据可应用于一些数据挖掘算法,如ID3决策树算法。     

Hamiltonian discretization of boundary control systems

A fundamental problem in the simulation and control of complex physical systems containing distributed-parameter components concerns finite-dimensional approximation. Numerical methods for partial differential equations (PDEs) usually assume the boundary conditions to be given, while more often than not the interaction of the distributed-parameter components with the other components takes place precisely via the boundary. On the other hand, finite-dimensional approximation methods for infinite-dimensional input-output systems (e.g., in semi-group format) are not easily relatable to numerical techniques for solving PDEs, and are mainly confined to linear PDEs. In this paper we take a new view on this problem by proposing a method for spatial discretization of boundary control systems based on a particular type of mixed finite elements, resulting in a finite-dimensional input-output system. The approach is based on formulating the distributed-parameter component as an infinite-dimensional port-Hamiltonian system, and exploiting the geometric structure of this representation for the choice of appropriate mixed finite elements. The spatially discretized system is again a port-Hamiltonian system, which can be treated as an approximating lumped-parameter physical system of the same type. In the current paper this program is carried out for the case of an ideal transmission line described by the telegrapher's equations, and for the two-dimensional wave equation.     

Optimal discretization of continuous-data control system

Two methods of simulating continuous-data systems by sampled-data models are presented. Sample-and-hold devices are inserted in an otherwise continuous-data system, and the input and the feedback gains are modified to make the response of the sampled-data model as close to that of the original system as possible. A point-by-point comparison method matches the state variables of the two systems at the sampling instants. Another method relies on the optimization of the sampled-data system with a quadratic performance index.     

A discretization algorithm based on a heterogeneity criterion

Discretization, as a preprocessing step for data mining, is a process of converting the continuous attributes of a data set into discrete ones so that they can be treated as the nominal features by machine learning algorithms. Those various discretization methods, that use entropy-based criteria, form a large class of algorithm. However, as a measure of class homogeneity, entropy cannot always accurately reflect the degree of class homogeneity of an interval. Therefore, in this paper, we propose a new measure of class heterogeneity of intervals from the viewpoint of class probability itself. Based on the definition of heterogeneity, we present a new criterion to evaluate a discretization scheme and analyze its property theoretically. Also, a heuristic method is proposed to find the approximate optimal discretization scheme. Finally, our method is compared, in terms of predictive error rate and tree size, with Ent-MDLC, a representative entropy-based discretization method well-known for its good performance. Our method is shown to produce better results than those of Ent-MDLC, although the improvement is not significant. It can be a good alternative to entropy-based discretization methods.     

新的基于最近邻聚类的属性离散化算法

连续属性离散化是知识发现研究中重要的预处理过程,基于最近邻聚类和粗集的相关理论,提出一种新的有监督的多属性离散化方法。该算法分两个阶段来处理,首先利用最近邻聚类动态调整聚类的类别数,生成初始聚类。然后基于类信息的相似性定义合并相似区间,减少了聚类区间。通过实例分析,该算法是非常有效的。     

基于统计相关系数的数据离散化方法

很多数据挖掘方法只能处理离散值的属性,因此,连续属性必须进行离散化。提出一种统计相关系数的数据离散化方法,基于统计相关理论有效地捕获了类-属性间的相互依赖,选取最佳断点。此外,将变精度粗糙集(VPRS)模型纳入离散化中,有效地控制数据的信息丢失。将所提方法在乳腺癌症诊断以及其他领域数据上进行了应用,实验结果表明,该方法显著地提高了See5决策树的分类学习精度。