Application of parallel mechanism in varistructured quadruped/biped human-carrying walking chair robot

For the existing problems of walking chair robot such as simple function,lower bearing capacity and not walking in complex environment,a novel varistructured quadruped / biped human-carrying walking chair robot is proposed.The proposed robot could be used as biped and quadruped walking chair robots.Considering the conversion of the walking chair robot from the quadruped to the biped or vice versa,6-UPS and 2-UPS+UP(U,P and S are universal joint,the prismatic pair,and sphere joint,respectively) parallel mechanisms are selected as the leg mechanism of the biped walking robot and quadruped walking robot,respectively.Combining the screw theory and theory of mechanism,the degrees of freedom of the leg mechanism and the body mechanism in diferent motion states are computed so as to meet the requirements of mechanism design.The motion characteristics of the 2-UPS+UP parallel mechanism which is the key part of the walking chair robot are analyzed.Then,the workspace of the moving platform is drawn and the efect of the structural parameters on the workspace volume is studied.Finally,it is found that the volume of the workspace of the moving platform is bigger when the side length ratio and the vertex angle ratio of the fxed platform and the moving platform which are isosceles triangles are close to 1.This study provides a theoretical foundation for the prototype development.     

Path tracking with quadruped walking machines using discontinuous gaits

Discontinuous gaits for walking machines offer great advantages over wave gaits, and they seem more adequate for following a path over irregular terrain. This paper, focused on quadruped walking robots, addresses the problem of following an arbitrary path using both discontinuous crab and turning gaits. First, the paper presents the algorithms to generate these gaits as local motions and highlights their advantages in comparison with continuous gaits. This comparison considers stability, velocity, power consumption and terrain adaptability. The algorithms for tracking an arbitrary trajectory using these gaits are then introduced, and some simulations and experimental results are reported.     

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.     

Adaptive dynamic walking of a quadruped robot using a neural system model

We are trying to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. In this paper, we integrate several reflexes, such as a stretch reflex, a vestibulospinal reflex and extensor/flexor reflexes, into a central pattern generator (CPG). We try to realize adaptive walking up and down a slope of 12°, walking over an obstacle 3 cm in height, and walking on terrain undulation consisting of bumps 3 cm in height with fixed parameters of CPGs and reflexes. The success in walking on such irregular terrain in spite of stumbling and landing on obstacles shows that the control method using a neural system model proposed in this study has the ability for autonomous adaptation to unknown irregular terrain. In order to clarify the role of a CPG, we investigate the relation between parameters of a CPG and the mechanical system by simulations and experiments. CPGs can generate stable walking suitable for the mechanical system by receiving inhibitory input as sensory feedback and generate adaptive walking on irregular terrain by receiving excitatory input as sensory feedback. MPEG footage of these experiments can be seen at: http://www.kimura.is.uec.ac.jp.     

Development of a quadruped walking robot AiDIN-III using biologically inspired kinematic analysis

This paper presents a bio-inspired mechanism design for a quadruped walking robot. The approach is derived from the observation on the behaviors of quadruped locomotion, skeletal structure, and the study on the stability of walking based on morphological analysis. In the first, we define the design parameters such as the dimensions of the body and limbs, the center of mass position, and locomotion mechanisms based on surveys on the literatures from biologists. Then, by using the parameters, we propose an useful framework for determining the design parameters of a quadruped walking robot. For implementations, we manufacture a dog-type self-contained quadruped walking robot, named AiDIN-III (Artificial Digitigrade for Natural Environment version III) and the effectiveness of the proposed idea is validated via experimental works.     

基于ATmega88和Delphi的双足竞步机器人设计

采用自主设计的PCB板和CDS5401舵机设计了一种双足竞步机器人,开发了基于ATmega88的机器人控制系统,基于仿生学原理的步态规划确定了机器人的运动序列。所设计的控制系统不仅操作简单,运行稳定可靠,而且人机交互界面友好,再扩展性强。最后,将所开发的机器人运用于中国机器人大赛双足竞步机器人比赛,取得了优异成绩。     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.     

Development and motion control of a biped walking robot based on passive walking theory

This research aims to develop the biped walking robot that can walk on the horizontal ground and improve walking efficiency by utilizing the theory of the passive walking robot, namely the pendulum principle. For that, two motors were installed on the hip of the robot to generate the control torques to perform a walking motion. The computer simulations with dynamic model were carried out to investigate the walking capability of the system. Experimental robot was developed considering the calculated results. The proportional control law was used in walking experiment. The robot can walk on the horizontal ground with the proposed method.     

Adaptive splitbelt treadmill walking of a biped robot using nonlinear oscillators with phase resetting

To investigate the adaptability of a biped robot controlled by nonlinear oscillators with phase resetting based on central pattern generators, we examined the walking behavior of a biped robot on a splitbelt treadmill that has two parallel belts controlled independently. In an experiment, we demonstrated the dynamic interactions among the robot mechanical system, the oscillator control system, and the environment. The robot produced stable walking on the splitbelt treadmill at various belt speeds without changing the control strategy and parameters, despite a large discrepancy between the belt speeds. This is due to modulation of the locomotor rhythm and its phase through the phase resetting mechanism, which induces the relative phase between leg movements to shift from antiphase, and causes the duty factors to be autonomously modulated depending on the speed discrepancy between the belts. Such shifts of the relative phase and modulations of the duty factors are observed during human splitbelt treadmill walking. Clarifying the mechanisms producing such adaptive splitbelt treadmill walking will lead to a better understanding of the phase resetting mechanism in the generation of adaptive locomotion in biological systems and consequently to a guiding principle for designing control systems for legged robots.     

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.     

An FCM modeling for using a priori knowledge: application study in modeling quadruped walking

Fuzzy cognitive map (FCM) is well established as a decision-making mechanism with many applications. This paper presents a new strategy for realistic FCM-based inference named input-sensitive FCM. The problem of lack of influence from initial concepts’ weights or priory knowledge on decision outputs is resolved. The results and comparisons with the existing inference models are included to evaluate the strength of the new strategy. The quadruped walking cycle is simulated as a case study for sanity testing and validation of the developed model in terms of realistic decision outputs.     

Dynamics modeling and analysis of a biped walking robot actuated by a closed-chain mechanism

We developed a new type of human-sized biped walking robot (BWR) driven by the closed-chain type of joint actuator. Each leg of the robot is composed of three pitch joints and one roll joint. In all, a 15 degree-of-freedom robot including four arm joints and three joints for the head was developed. The BWR was developed to walk autonomously such that all leg joints are actuated by small 90 W dc motors/drivers and dc batteries and controllers which are boarded. The joint actuator for the BWR is composed of the four-bar-link mechanism driven by the ball screw which has high strength and high gear ratio. A dynamics modeling of the developed BWR for forward walking is presented in which the revolute joint dynamics are transformed into the prismatic joint dynamics of the ball screw. Also, an analysis on the four-bar-link mechanism applied to the joint actuator and on the structure of the BWR is shown. The design specification of the actuating motor for the BWR is analyzed through the torque analysis of the four-bar-link actuator. Through walking experiments of the BWR, the walking performance and trajectory tracking ability is shown. © 2004 Wiley Periodicals, Inc.     

3D stable biped walking control and implementation on real robot

A combination of walking control methods was proposed and implemented on a biped robot. The LIPM-based model predictive control (MPC) was adopted to generate a basic stable walking pattern. The stability of pitch and yaw rotation was improved through pitch and yaw momentum control as a supplementation of MPC. It is found that biped robot walking tends to deviate from the planned walking direction if not considering the rotation friction torque in yaw axis under the support foot. There are basically two methods to control yaw momentum, waist and swing arms rotation control. However, the upper body is often needed to accomplish other tasks. Therefore, a yaw momentum control method based on swing leg dynamics was proposed. This idea does not depend on upper body’s motion and is highlighted in this paper. Through experiments, the feasibility of the combination of the control methods proved to be practical in keeping biped robot walking stable both in linear and rotation motion. The pros and cons of the yaw momentum control method were also tested and discussed through comparison experiments, such as walking on flat and uneven terrain, walking with different payloads.     

Switching and PI control of walking motions of planar biped walkers

A companion paper has addressed the problem of designing controllers that induce exponentially stable, periodic walking motions at a fixed walking rate for a planar, biped robot with one degree of underactuation. This note provides two additional control features: 1) the ability to compose such controllers to obtain walking at several discrete walking rates with guaranteed stability during the transitions; and 2) the ability to regulate the average walking rate to a continuum of values.     

Inverse kinematics and inverse dynamics for control of a biped walking machine

Analytical techniques are presented for the motion planning and control of a 12 degree-of-freedom biped walking machine. From the Newton-Euler equations, joint torques are obtained in terms of joint trajectories, and the inverse dynamics are developed for both the single-support and double-support cases. Physical admissibility of the biped trajectory is characterized in terms of the equivalent force-moment and zero-moment point. This methodology has been used to obtain reference inputs and implement the feedforward control of walking robots. A simulation example illustrates the application of the techniques to plan the forward-walking trajectory of the biped robot. The implementation of a prototype mechanism and controller is also described.     

Using efference copy and a forward internal model for adaptive biped walking

To behave properly in an unknown environment, animals or robots must distinguish external from self-generated stimuli on their sensors. The biologically inspired concepts of efference copy and internal model have been successfully applied to a number of robot control problems. Here we present an application of this for our dynamic walking robot RunBot. We use efference copies of the motor commands with a simple forward internal model to predict the expected self-generated acceleration during walking. The difference to the actually measured acceleration is then used to stabilize the walking on terrains with changing slopes through its upper body component controller. As a consequence, the controller drives the upper body component (UBC) to lean forwards/backwards as soon as an error occurs resulting in dynamical stable walking. We have evaluated the performance of the system on four different track configurations. Furthermore we believe that the experimental studies pursued here will sharpen our understanding of how the efference copies influence dynamic locomotion control to the benefit of modern neural control strategies in robots.     

Stability analysis and time-varying walking control for an under-actuated planar biped robot

This paper presents two walking controllers for a planar biped robot with unactuated point feet. The control is based on the tracking of reference motions expressed as a function of time. First, the reference motions are adapted at each step in order to create a hybrid zero dynamic (HZD) system. Next, the stability of the walking gait under closed-loop control is evaluated with the linearization of the restricted Poincaré map of the HZD. When the controlled outputs are selected to be the actuated coordinates, most periodic walking gaits for this robot are unstable, that is, the eigenvalues of the linearized Poincaré map (ELPM) is larger than one. Therefore, two control strategies are explored to produce stable walking. The first strategy uses an event-based feedback controller to modify the ELPM and the second one is based on the choice of controlled outputs. The stability analysis show that, for the same robot and for the same reference trajectory, the stability of the walking (or ELPM) can be modified by some pertinent choices of controlled outputs. Moreover, by studying some walking characteristics of many stable cases, a necessary condition for stable walking is proposed. It is that the height of swing foot is nearly zero at the desired moment of impact. Based on this condition, the duration of the step is almost constant in presence of initial error, so a method for choosing controlled outputs for the second controller is given. By using this method, two stable domains for the controlled outputs selection are obtained.     

Central pattern generator parameter search for a biped walking robot using nonparametric estimation based Particle Swarm Optimization

A parameter search for a Central Pattern Generator (CPG) for biped walking is difficult because there is no methodology to set the parameters and the search space is broad. These characteristics of the parameter search result in numerous fitness evaluations. In this paper, nonparametric estimation based Particle Swarm Optimization (NEPSO) is suggested to effectively search the parameters of CPG. The NEPSO uses a concept experience repository to store a previous position and the fitness of particles in a PSO and estimated best position to accelerate a convergence speed. The proposed method is compared with PSO variants in numerical experiments and is tested in a three dimensional dynamic simulator for bipedal walking. The NEPSO effectively finds CPG parameters that produce a gait of a biped robot. Moreover, NEPSO has a fast convergence property which reduces the evaluation of fitness in a real environment. Recommended by Editorial Board member Euntai Kim under the direction of Editor Jae-Bok Song. Jeong-Jung Kim received the B.S. degree in Electronics and Information Engineering from Chonbuk National University in 2006 and the M.S. degree in Robotics from Korea Advanced Institute of Science and Technology in 2008. He is currently working toward a Ph.D. at the Korea Advanced Institute of Science and Technology. His research interests include biologically inspired robotics and machine learning. Jun-Woo Lee received the B.S. degree in Electronics, Electrical and Communication Engineering from Pusan National University in 2007. He is currently working toward an M.S. in the Korea Advanced Institute of Science and Technology. His research interests include swarm intelligence and machine learning. Ju-Jang Lee was born in Seoul, Korea, in 1948. He received the B.S. and M.S. degrees from Seoul National University, Seoul, Korea, in 1973 and 1977, respectively, and the Ph.D. degree in Electrical Engineering from the University of Wisconsin, in 1984. From 1977 to 1978, he was a Research Engineer at the Korean Electric Research and Testing Institute, Seoul. From 1978 to 1979, he was a Design and Processing Engineer at G. T. E. Automatic Electric Company, Waukesha, WI. For a brief period in 1983, he was the Project Engineer for the Research and Development Department of the Wisconsin Electric Power Company, Milwaukee. He joined the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, in 1984, where he is currently a Professor. In 1987, he was a Visiting Professor at the Robotics Laboratory of the Imperial College Science and Technology, London, U.K. From 1991 to 1992, he was a Visiting Scientist at the Robotics Department of Carnegie Mellon University, Pittsburgh, PA. His research interests are in the areas of intelligent control of mobile robots, service robotics for the disabled, space robotics, evolutionary computation, variable structure control, chaotic control systems, electronic control units for automobiles, and power system stabilizers. Dr. Lee is a member of the IEEE Robotics and Automation Society, the IEEE Evolutionary Computation Society, the IEEE Industrial Electronics Society, IEEK, KITE, and KISS. He is also a former President of ICROS in Korea and a Counselor of SICE in Japan. He is a Fellow of SICE and ICROS. He is an Associate Editor of IEEE Transactions on Industrial Electronics and IEEE Transactions on Industrial Informatics.     

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.