Dynamically balanced optimal gaits of a ditch-crossing biped robot

This paper deals with the generation of dynamically balanced gaits of a ditch-crossing biped robot having seven degrees of freedom (DOFs). Three different approaches, namely analytical, neural network (NN)-based and fuzzy logic (FL)-based, have been developed to solve the said problem. The former deals with the analytical modeling of the ditch-crossing gait of a biped robot, whereas the latter two approaches aim to maximize the dynamic balance margin of the robot and minimize the power consumption during locomotion, after satisfying a constraint stating that the changes of joint torques should lie within a pre-specified value to ensure its smooth walking. It is to be noted that the power consumption and dynamic balance of the robot are also dependent on the position of the masses on various links and the trajectory followed by the hip joint. A genetic algorithm (GA) is used to provide training off-line, to the NN-based and FL-based gait planners developed. Once optimized, the planners will be able to generate the optimal gaits on-line. Both the NN-based and FL-based gait planners are able to generate more balanced gaits and that, too, at the cost of lower power consumption compared to those yielded by the analytical approach. The NN-based and FL-based approaches are found to be more adaptive compared to the other approach in generating the gaits of the biped robot.     

无动力双足步行机器人控制策略与算法

本文研究无动力双足步行机器人的建模、分析与控制问题. 基于能量的控制增加了机器人行走极限环的稳定性、鲁棒性, 扩大了极限环的收敛域; 角度不变控制使机器人的稳定行走步态摆脱了地面倾斜角度的限制; 把基于能量的控制与角度不变控制结合起来, 可以实现在不同倾斜角度地面上行走模式的切换. 基于能量的行走平均速度控制方法在平均速度与目标能量之间建立了联系, 能使机器人的行走产生新的稳定步态. 最后, 对无动力双足步行机器人的研究前景做了展望.     

Comparison of different gaits with rotation of the feet for a planar biped

Fast human walking includes a phase where the stance heel rises from the ground and the stance foot rotates about the stance toe. This phase where the biped becomes under-actuated is not present during the walk of humanoid robots. The objective of this study is to determine if this phase is useful to reduce the energy consumed in the walking. In order to study the efficiency of this phase, six cyclic gaits are presented for a planar biped robot. The simplest cyclic motion is composed of successive single support phases with flat stance foot on the ground. The most complex cyclic motion is composed of single support phases that include a sub-phase of rotation of the stance foot about the toe and of finite time double support phase. For the synthesis of these walking gaits, optimal motions with respect to the torque cost, are defined by taking into account given performances of actuators. It is shown that for fast motions a foot rotation sub-phase is useful to reduce the criteria cost. In the optimization process, under-actuated phase (foot rotation phase), fully-actuated phase (flat foot phase) and over-actuated phase (double support phase) are considered.     

Ascending and descending stairs for a biped robot

This paper synthesizes an efficient walking pattern for a practical biped robot when ascending and descending stairs. The main features of the biped robot include variable length legs and a translatable balance weight in the body. The biped robot's walk is a mixture of both statically stable and dynamically stable modes and relies on some degrees of static stability provided by large feet and by carefully controlling the center of gravity's position. The paper describes the design and experiment of a 7-DOF practical biped which is capable of ascending and descending stairs, and the synthesis of an efficient walking gait for ascending and descending stairs. Our biped robot is one of the few biped walking machines capable of ascending and descending stairs     

A hybrid SOF-PID controller for a MIMO biped robot

The application of the hybrid self-organizing fuzzy (SOF) PID controller to a multiinput multioutput nonlinear biped robot is studied in this article. The SOF-PID controller was initially studied by H.B. Kazemian in 1998. Actually, his SOF-PID controller has limits. The supervisory capacity of the SOF-PID controller can adjust only certain kinds of parameters. Here the hybrid SOF-PID controller is introduced to tune some kinds of parameters, and it was tested on a MIMO biped robot. In the experiment, the hybrid SOF-PID controller shows a better performance than the SOF-PID. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

Design of walking gaits for Tao-Pie-Pie,a small humanoid robot

A new way for multi-axis robot trajectory planning using a single cubic spline incorporating velocity and acceleration clipping is presented. Equations for velocity and acceleration clipping employing the cubic spline function for a single axis are derived. A robot tool-tip velocity vector magnitude clipping algorithm is proposed. Implementation for a fly-by and contour following trajectory control is discussed.     

变长度柔性双足机器人行走控制及稳定性分析

针对传统双足机器人模型缺少脚质量和躯干的问题,提出考虑摆动腿动态及躯干影响的柔性双足机器人模型,并对其行走控制及稳定性进行研究。首先,建立系统的动力学模型并采用欧拉-拉格朗日法推导了系统的动力学方程;同时,在弹簧负载倒立摆（SLIP）模型的基础上添加刚性躯干、脚质量及采用变长度伸缩腿,充分考虑躯干及摆动腿动力学对机器人行走步态的影响;其次,设计基于变长度腿的反馈线性化控制器来跟踪目标轨迹,以及调节摆动腿和躯干的姿态;最后,利用Newton-Raphson迭代法和庞加莱映射分析机器人的不动点及轨道稳定性条件,并在理论分析的基础上进行仿真。仿真结果表明,所提控制器可以实现机器人的周期行走,对外界干扰具有良好的鲁棒性,且雅可比矩阵所有特征值的模均小于1,能形成稳定的极限环,证明系统是轨道稳定的。     

Sensor system of a small biped entertainment robot

SDR-4X II is the latest prototype model of a small biped entertainment robot. It is the improved model of SDR-4X. In this paper we report on the sensing system of this robot, which is important and essential for a small biped entertainment robot which will be used in the home environment. One technology is the design of the motion sensing system, i.e. the inclination sensor system and the force sensor system which obtains the inclination of the trunk and the foot with force. Another technology is the real-world sensing system. One aspect is the touch sensing system. The robot is used in a normal home environment, so we should strongly consider the safety aspects for human. Another is the vision sensor system. The configuration and the distance image acquisition are explained. Next is the audio sensor system which obtains the sound and the voice information. The hardware system and the direction recognition are explained. These sensing systems are the key to making the biped robot walking and dynamic motion highly stable, and understanding the real-world around the robot.     

Reinforcement learning for a biped robot to climb sloping surfaces

A neural network mechanism is proposed to modify the gait of a biped robot that walks on sloping surfaces using sensory inputs. The robot climbs a sloping surface from a level surface with no priori knowledge of the inclination of the surface. By training the neural network while the robot is walking, the robot adjusts its gait and finally forms a gait that is as stable as when it walks on the level surface. The neural network is trained by a reinforcement learning mechanism while proportional and integral (PI) control is used for position control of the robot joints. Experiments of static and pseudo dynamic learning are performed to show the validity of the proposed reinforcement learning mechanism. © 1997 John Wiley & Sons, Inc.     

Position-based impedance control of a biped humanoid robot

This paper describes position-based impedance control for biped humanoid robot locomotion. The impedance parameters of the biped leg are adjusted in real-time according to the gait phase. In order to reduce the impact/contact forces generated between the contacting foot and the ground, the damping coefficient of the impedance of the landing foot is increased largely during the first half double support phase. In the last half double support phase, the walking pattern of the leg changed by the impedance control is returned to the desired walking pattern by using a polynomial. Also, the large stiffness of the landing leg is given to increase the momentum reduced by the viscosity of the landing leg in the first half single support phase. For the stability of the biped humanoid robot, a balance control that compensates for moments generated by the biped locomotion is employed during a whole walking cycle. For the confirmation of the impedance and balance control, we have developed a life-sized humanoid robot, WABIAN-RIII, which has 43 mechanical d.o.f. Through dynamic walking experiments, the validity of the proposed controls is verified.     

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.     

二足机器人之动态平衡研究

主要探讨二足机器人（biped robots）行走或受到外力干扰时,通过动态平衡控制使机器人行走更趋稳定,并增强站立时稳定性．二足机器人动态平衡之实现,主要是将动态平衡控制程序撰写于Nios Ⅱ发展环境中,当二足机器人行走时,利用脚底压力传感器取得压力值,运算及判断二足机器人实际重心是否落在二足机器人支撑多边形范嗣内,并计算实际重心与期望重心之误差,以模糊控制器将二足机器人重心控制于支撑多边形范围内,使二足机器人行走时能够更加稳定,实验结果表明该方法是有效的．     

Toward a human-like biped robot with compliant legs

Conventional models of bipedal walking generally assume rigid body structures, while elastic material properties seem to play an essential role in nature. On the basis of a novel theoretical model of bipedal walking, this paper investigates a model of biped robot which makes use of minimum control and elastic passive joints inspired from the structures of biological systems. The model is evaluated in simulation and a physical robotic platform by analyzing the kinematics and ground reaction force. The experimental results show that, with a proper leg design of passive dynamics and elasticity, an attractor state of human-like walking gait patterns can be achieved through extremely simple control without sensory feedback. The detailed analysis also explains how the dynamic human-like gait can contribute to adaptive biped walking.     

改进的RRT-Connect双足机器人路径规划算法

针对当组态空间内存在大量的窄道时,快速搜索随机树算法(RRT)难以取得连通路径的问题,提出了一种改进的RRT-Connect算法。该算法利用改进的桥梁检测算法来识别和采样窄道,使得路径规划在窄道内能轻易取得连通性;同时将RRT-Connect算法与任意时间算法相结合,显著地减少了RRT-Connect算法的移动代价。每个算法分别运行100次,与RRT-Connect算法相比,改进后的算法成功次数由34提高到93,规划时间由9.3s减少到4.2s。双足机器人的仿真实验结果表明,该算法能在窄道内取得优化路径,同时可以有效地提高路径规划的效率。     

Sensory-based walking motion instruction for biped humanoid robot

This paper describes a sensory-based biped walking motion instruction strategy. Visual and auditory sensors are employed to generate walking patterns according to human orders and to memorize various complete walking patterns effectively and systematically. The motion of lower-limbs for locomotion is created by an online pattern generator based on the sensory information. At the same time, the motion of the trunk and the waist for stability is generated online by a balance control method. Combining these locomotive and balance motions, a complete walking pattern is hierarchically constructed and memorized on a database. The walking instruction is conducted through computer simulation, and its effectiveness is verified.     

双足机器人实时障碍检测视觉系统

提出一种双足步行机器人的实时障碍检测视觉系统．基于图像平面与机器人行走地面之间的映射变换矩阵的唯一性准则，判别图像中的像点是否位于地面上，高于或低于地面的点被认为是障碍点，为减少实际行走过程中系统外部和内部参数变化对映射变换矩阵的影响，系统加入了在线校正映射变换矩阵模块．在提取出障碍物体边缘后，通过对其三维信息的简单恢复，建立了机器人行走空间的障碍投影图．该系统计算量小，可靠性强，能基本满足双足步行机器人实时避障的要求。     

Neuro-fuzzy gait synthesis with reinforcement learning for a biped walking robot

 A reinforcement learning-based neuro-fuzzy gait synthesizer, which is based on the GARIC (Generalized Approximate Reasoning for Intelligent Control) architecture, is proposed for the problem of biped dynamic balance. We modify the GARIC architecture to enable it to generate the trunk trajectory in both sagittal and frontal plane. The proposed gait synthesizer is trained by reinforcement learning that uses a multi-valued scalar signal to evaluate the degrees of failure or success for the biped locomotion by means of the ZMP (Zero Moment Point). It can form the initial dynamic balancing gait from linguistic rules, which are obtained from human intuitive balancing knowledge and biomechanics studies, and accumulate dynamic balancing knowledge through reinforcement learning, and thus constantly improve its gait during walking. The feasibility of the proposed method is verified through a 5-link biped robot simulation.     

两足外骨骼机器人足底压力测量系统

为实现两足外骨骼机器人行走过程中的步态识别,需精确、可靠地获取其足底压力载荷的分布情况。研制一种高灵敏度具有强抗偏载能力的小型轮辐式足底压力传感器,并针对该传感器输出电压只有几十微伏的微弱信号特点设计制作了具有斩波自稳零功能的多路前置信号放大调理电路板。为减小温度等因素产生的非线性误差,设计了传感器恒电流源供电模块。系统采用基于PC的控制器,多通道信号高精度同步采样,通过实际样机试验表明电路实现高增益放大的同时输出噪声峰峰值小于3 mV,且长时间样机试验,信号几乎不存在零漂,具有较好的稳定性。系统结构合理,可靠性高,可适用于仪表信号的处理。     

Optimization and evaluation of swing leg retraction for a hydraulic biped robot

To improve the locomotion performance of legged robots, the swing leg retraction (SLR) technique is investigated in a hydraulic biped robot. First, the influence of SLR on the locomotion performance of the hydraulic biped robot is analyzed in theory and simulations based on an extended spring load inverted pendulum model. The influence contains three performance indicators: energy loss/effiency, friction/slipping, and impact/compliance. Second, by synthesizing three performance indicators, using unified objective method and particle swarm optimization algorithm, the optimal SLR rate for gait planning based on Bezier curve is addressed. Finally, experiments are implemented to validate the effectiveness and feasibility of proposed method. And, the results show that the SLR technique is useful to reduce the impact force, improve the robot's locomotion stability and make room for impedance performance improvement of compliance controller. This research provides an insight for locomotion control of hydraulic legged robots.     

双足机器人稳定行走的仿人预测控制研究

针对双足机器人的稳定行走,提出了一种新的仿人预测控制在线步行模式生成方法。把期望零力矩点（ZMP）分解成离线规划好的参考ZMP和实时变化的可变ZMP之和,通过预测控制和其逆系统共同作用对质心运动进行控制,从而生成具有自适应性的步行模式。但单一的预测控制系统对诸如矩形齿状扰动的可变ZMP的跟踪存在较大的误差,结合仿人智能控制对误差的强抑制能力,设计了与预测控制相结合的仿人预测控制系统。仿真实验验证对矩形齿状扰动的可变ZMP,仿人预测系统也能实现较好的跟踪。