A gait study for a one-leg-disabled hexapod robot

—As a remarkably strong point of a hexapod walking robot, it is considered that even if one of the six legs is disabled, static walking may be maintained by the remaining five legs. However, to maintain the static stability at maximum, a gait study for five-legged walking is a necessary factor. Hence, this paper describes a method of gait study for such a situation. Since it is very difficult to find a suitable gait by use of an analytical method without any model, such as a model based on insects' walking, we employed a programming method with the help of recent powerful computers. Some devices are applied to reduce the number of computations. As a result, we have obtained two kinds of gaits which can maintain the gait stability margin at a high level for a duty factor in the range of 0.6β < 1.     

四腿机器人步态控制与仿真研究

本文分析了四腿机器人行走步态,依据现有机器人部件设计了行走控制程序,其中采用腿部摆转,起落分时控制方法,实现了机器人前进、后退、转向等典型动作,机器人最后经ADAMS进行机构运动仿真,仿真结果准确,可用于指导该机器人的结构优化与程序开发.     

足式机器人SLIP模型向上跳跃台阶的运动控制

由于存在地势起伏,台阶对足式机器人运动稳定性会带来较大挑战.弹簧负载倒立摆模型(SLIP)作为研究足式机器人的优良模板,能否完成向上跳跃台阶的动作与其腿部摆角,起跳位置和跳跃高度都有密切的关系.由于调整模型腿部摆角规律容易引发运动失效,故本文在算法中引入虚拟弹簧腿,根据虚拟弹簧腿的运行规律确定合理起跳位置,根据起跳位置来控制系统跳跃高度进而完成跳跃台阶的动作.最后利用仿真软件进行多组仿真,结果表明本文算法对起跳区间划分合理,对起跳高度控制精准,能够实现SLIP模型跳跃台阶前后的稳定运动.     

电磁式爬壁机器人平台

本文介绍了一种新型电磁式爬壁机器人平台。机器人平台从客观需求出发,利用电磁铁可以吸附铁质物体的原理,实现机器人在铁质壁面上竖直攀爬。机器人平台以单片机为控制核心,控制四只仿生脚的行动和电磁铁的吸附,由无线控制器实现远程控制。平台搭载多种传感器,以检测机器人周围的环境状态,并应用无线传输技术,将传感器监测数据时时传回控制电脑。还可由电脑控制,利用机器人上加装的机械臂,完成简单操作。本项目作品可以应用于强热辐射、浓烟、污染气体等复杂环境的场所实施远程测控,也可以应用于船体、高炉检测等方面。     

基于离散化的六足机器人自由步态规划

为精细模仿生物步态,充分发挥六足机器人运动潜能,本文在离散化机器人足端轨迹的基础上,融合中枢模式发生器(central pattern generator,CPG)模型与反射模型的核心思想,建立了离散化步态模型,结合稳定性分析,构建了机器人稳定的位置状态空间,将复杂的步态规划问题转化为稳定的位置状态空间中位置状态间的排序问题,在此基础上,提出了一种新的自由步态生成算法,并基于平均稳定裕量对该算法进行了优化.样机步态实验结果表明,自由步态生成算法与自由步态优化算法均可生成在一定程度上符合生物运动特点的稳定步态,实现机器人运动过程中速度的动态调整,跨越宽度为步距的障碍,且基于平均稳定裕量的自由步态优化算法生成步态的稳定性要远大于自由步态生成算法.     

Planar legged walking of a passive-spine hexapod robot

This paper proposes a new legged walking method for a novel passive-spine hexapod robot. This robot consists of several body segments connected by passive body joints. Each of the body segments carries two 1-DoF (degree of freedom) actuated legs. The robot is capable of achieving planar legged walking by rapidly abducting and adducting its legs. To model the mobility of a robot based on this simple design, the candidate configurations from all possible configurations are first selected in a mobility analysis of the robot based on the screw theory. All the feasible sequences of these candidate configurations are then searched to form planar locomotion gaits. Next, locomotive performance of the gaits is analyzed. Finally, the proposed locomotion design and gait planning methods are verified through simulations and experiments.     

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.     

Gait transition and modulation in a quadruped robot: A brainstem-like modulation approach

In this article, we propose a bio-inspired architecture for a quadruped robot that is able to initiate/stop locomotion; generate different gaits, and to easily select and switch between the different gaits according to the speed and/or the behavioral context. This improves the robot stability and smoothness while locomoting.We apply nonlinear oscillators to model Central Pattern Generators (CPGs). These generate the rhythmic locomotor movements for a quadruped robot. The generated trajectories are modulated by a tonic signal, that encodes the required activity and/or modulation. This drive signal strength is mapped onto sets of CPG parameters. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori.The system is implemented in a simulated and real AIBO robot. Results demonstrate the adequacy of the architecture to generate and modulate the required coordinated trajectories according to a velocity increase; and to smoothly and easily switch among the different motor behaviors.     

一种有腿机器人步态轨迹生成算法

目前存在一类有腿机器人,由于其底层动力学控制参数难于获取,行走设计无法使用已有的控制方法,现有的基于建模的步态存在缺乏完善规划,固定规划步态与实际步态相差较大的问题,针对这个问题,提出一种使用曲线拟合生成步态轨迹的想法,通过引入遗传算法,让机器人能自主的搜索良好的行走步态轨迹,在四足步行机器人平台上取得了良好的实验结果.     

Dynamic Analysis Tool for Legged Robots

The paper introduces a systematic approach for dealing with legged robot mechanism analysis. First, we briefly summarize basic mathematical tools for studying the dynamics of these multi-loop and parallel mechanisms using a unified spatial formulation which is useful for computer algorithms. The dynamic behavior analysis is based on two stages. The first one deals with establishing the equations of motion of the whole mechanism including legs tip impact effects and allowing us to solve the direct and inverse dynamic problems. The second concerns the feet–ground interaction aspect which is one of the major problem in the context of dynamic simulation for walking devices. We focus on the phenomenon of contact by introducing a general model for dynamic simulation of contacts between a walking robot and ground. This model considers a force distribution and uses an analytical form for each force depending only on the known state of the robot system. Finally, some simulation results of biped robot are given. The simulation includes all phenomena that may occur during the locomotion cycle: impact, transition from impact to contact, contact during support with static friction, transition from static to sliding friction and sliding friction.     

Design and control of a climbing robot based on hot melt adhesion

Robust climbing in unstructured environments has been one of the long-standing challenges in robotics research. Among others, the control of large adhesion forces is still an important problem that significantly restricts the locomotion performance of climbing robots. The main contribution of this paper is to propose a novel approach to autonomous robot climbing which makes use of hot melt adhesion (HMA). The HMA material is known as an economical solution to achieve large adhesion forces, which can be varied by controlling the material temperature. For locomotion on both inclined and vertical walls, this paper investigates the basic characteristics of HMA material, and proposes a design and control of a climbing robot that uses the HMA material for attaching and detaching its body to the environment. The robot is equipped with servomotors and thermal control units to actively vary the temperature of the material, and the coordination of these components enables the robot to walk against the gravitational forces even with a relatively large body weight. A real-world platform is used to demonstrate locomotion on a vertical wall, and the experimental result shows the feasibility and overall performances of this approach.     

Gait Adaptation in a Quadruped Robot

A newborn foal can learn to walk soon after birth through a process of rapid adaptation acting on its locomotor controller. It is proposed here that this kind of adaptation can be modeled as a distributed system of adaptive modules (AMs) acting on a distributed system of adaptive oscillators called Adaptive Ring Rules (ARRs), augmented with appropriate and simple reflexes. It is shown that such a system can self-program through interaction with the environment. The adaptation emerges spontaneously as several discrete stages: Body twisting, short quick steps, and finally longer, coordinated stepping.This approach is demonstrated on a quadrupedal robot. The result is that the system can learn to walk several minutes after inception.     

基于CPG的六足机器人运动步态控制方法

中枢模式发生器（CPG）在六足机器人的运动步态控制中起着至关重要的作用。为了研究六足机器人的运动控制方法,首先基于仿生学原理设计了六足机器人的机械结构,并在虚拟样机软件ADAMS中搭建其三维模型;其次选择Hopf振荡器作为CPG单元,并改进了振荡器模型;然后设计了六足机器人的CPG网络拓扑结构,包含单腿关节映射函数方案和腿间CPG环形耦合网络方案,并对其进行了改进;最后通过ADAMS和MATLAB联合仿真实验,验证了所设计六足机器人的运动稳定性和CPG控制方案的可行性与有效性。仿真结果表明,该方法能够满足六足机器人不同运动步态的控制需求,对六足机器人的运动控制具有一定的实际应用价值。     

Sampling‐based hierarchical motion planning for a reconfigurable wheel‐on‐leg planetary analogue exploration rover

Reconfigurable mobile planetary rovers are versatile platforms that may safely traverse cluttered environments by morphing their physical geometry. Planning paths for these adaptive robots is challenging due to their many degrees of freedom, and the need to consider potentially continuous platform reconfiguration along the length of the path. We propose a novel hierarchical structure for asymptotically optimal (AO) sampling‐based planners and specifically apply it to the state‐of‐the‐art Fast Marching Tree (FMT*) AO planner. Our algorithm assumes a decomposition of the full configuration space into multiple subspaces, and begins by rapidly finding a set of paths through one such subspace. This set of solutions is used to generate a biased sampling distribution, which is then explored to find a solution in the full configuration space. This technique provides a novel way to incorporate prior knowledge of subspaces to efficiently bias search within existing AO sampling‐based planners. Importantly, probabilistic completeness and asymptotic optimality are preserved. Experimental results in simulation are provided that benchmark the algorithm against state‐of‐the‐art sampling‐based planners without the hierarchical variation. Additional experimental results performed with a physical wheel‐on‐leg platform demonstrate application to planetary rover mobility and showcase how constraints such as actuator failures and sensor pointing may be easily incorporated into the planning problem. In minimizing an energy objective that combines an approximation of the mechanical work required for platform locomotion with that required for reconfiguration, the planner produces intuitive behaviors where the robot dynamically adjusts its footprint, varies its height, and clambers over obstacles using legged locomotion. These results illustrate the generality of the planner in exploiting the platform's mechanical ability to fluidly transition between various physical geometric configurations, and wheeled/legged locomotion modes, without the need for predefined configurations.     

Weaver: Hexapod robot for autonomous navigation on unstructured terrain

Legged robots are an efficient alternative for navigation in challenging terrain. In this paper we describe Weaver, a six‐legged robot that is designed to perform autonomous navigation in unstructured terrain. It uses stereo vision and proprioceptive sensing based terrain perception for adaptive control while using visual‐inertial odometry for autonomous waypoint‐based navigation. Terrain perception generates a minimal representation of the traversed environment in terms of roughness and step height. This reduces the complexity of the terrain model significantly, enabling the robot to feed back information about the environment into its controller. Furthermore, we combine exteroceptive and proprioceptive sensing to enhance the terrain perception capabilities, especially in situations in which the stereo camera is not able to generate an accurate representation of the environment. The adaptation approach described also exploits the unique properties of legged robots by adapting the virtual stiffness, stride frequency, and stride height. Weaver's unique leg design with five joints per leg improves locomotion on high gradient slopes, and this novel configuration is further analyzed. Using these approaches, we present an experimental evaluation of this fully self‐contained hexapod performing autonomous navigation on a multiterrain testbed and in outdoor terrain.     

基于约束满足的多目标双足机器人动态步态参数优化*

目前的步态优化算法仅仅实现了对单一目标的优化,把双足机器人步态优化看做是多目标优化问题,构建了衡量稳定性、能量消耗、步行速度三个目标评价函数。考虑到直接对多个目标加权求和的方法不能很好地处理多目标问题,提出一种新的基于约束满足的多目标步态参数优化算法,其思想是把基于惩罚函数的SPEA2(strength Pareto evolutionary algorithm2 )应用到多目标双足机器人动态步态参数优化问题上,规划出了同时满足这三个目标的动态优化步态。通过仿真实验表明了算法的有效性。     

基于群体爬山策略的混合粒子群优化算法

针对粒子群优化算法（PSO）在求解高维复杂优化问题时存在搜索精度不高和易陷入局部最优解的缺陷,借鉴混合蛙跳算法（SFLA）的群体爬山思想,提出一种基于群体爬山策略的混合粒子群优化算法（CMCPSO）,并证明了CMCPSO算法的全局收敛性。对四个典型高维连续优化函数的求解表明,该算法不仅保持了PSO算法的快速收敛能力,而且吸收了SFLA算法局部精细搜索和保持种群多样性的优点,具有良好的全局收敛性。     

基于体感的仿人机器人步态学习与控制

针对现有理想化步态动力学模型规划方法复杂、人为指定参数过多、计算量大的问题,提出一种基于体感数据学习人体步态的仿人机器人步态生成方法。首先,用体感设备收集人体骨骼信息,基于最小二乘拟合方法建立人体关节局部坐标系;其次,搭建人体与机器人映射的运动学模型,根据两者间主要关节映射关系,生成机器人关节转角轨迹,实现机器人对人类行走姿态的学习;然后,基于零力矩点(ZMP)稳定性原则,对机器人脚踝关节转角采用梯度下降算法进行优化控制;最后,在步态稳定性分析上,提出使用安全系数来评价机器人行走稳定程度的方法。实验结果表明,步行过程中安全系数保持在0~0.85,期望为0.4825,ZMP接近于稳定区域中心,机器人实现了仿人姿态的稳定行走,证明了该方法的有效性。     

自适应变步长菌群优化算法

针对菌群优化算法由于步长固定导致探索能力不强等缺陷,应用聚类思想自适应计算并调整细菌的趋化步长,体现了菌群之间的协同性和智能性行为,有效地提高算法的性能,比如探索能力和开发能力,特别是局部搜索和求精能力。在使用10个复杂的Benchmark函数所进行的对比实验中,所提出的算法在搜索能力和效率等方面优于其他典型算法的比率达到60%~90%,验证了改进算法是一种具有竞争力的优化算法。     

仿蟹机器人步态分析与仿真

在仿蟹机器人的行走控制中,步态的选择对机器人的稳定快速行走具有至关重要的作用。本文对仿蟹八足机器人的基本步态进行了分类,并进一步对八足波形步态进行分析,得出八足步行机器人在采用双四足步态的行走方式时,既可以满足速度的要求,又可以保证机器人的稳定性。通过计算机软件ADAMS对所选步态进行全局仿真,结果验证了步态规划的合理性,同时得到了机器人相关物理量的变化曲线,为进一步选择电机,分析机器人系统的动态特性提供了依据。