Control Approach for Legged Robots with Fast Gaits

A constructive control approach is proposed for legged robots with fast dynamic gaits. These systems interact intermittently with the environment. Our approach is based on Controlled Limit Cycles (CLC) and stabilizes periodic system trajectories. The designed control law generates (on-line) the desired trajectories and control input.     

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.     

一种多足步行机器人行走状态分析模型

结合步行机器人行走的动力学特性,通过对机器人的加速度传感器信息进行离散傅立叶变换,建立了行走相关特征值的概率模型.通过使用马氏距离作为判定标准,对步行机器人的行走稳定性给出定量描述.四足步行机器人平台上的实验结果表明,该模型能够实时反映机器人的行走特性,帮助机器人在行走状态受环境影响发生改变时,根据行走特征及时调整运动,保证其稳定性.     

腿式机器人的研究综述

分析了国内外腿式机器人的研究现状,讨论了腿式机器人在机械结构、稳定性和控制算法方面的现有研究方法,给出了腿式机器人研究存在的问题,展望了腿式机器人的发展方向．     

足式机器人在非结构地形中的姿态求解算法

为了改进传统足式机器人姿态求解算法的不足,提出了一种新型的适用于非结构地形的姿态求解方法.该算法将动力学分析得到机体运动加速度信息与惯性测量单元（IMU）的信息相融合,通过卡尔曼滤波器计算机器人机体的姿态信息.所提的算法也适用于机器人机体存在冲击力的情况。为了验证算法的有效性,对两款典型的足式机器人在非结构地形中的运动进行了仿真,结果表明提出的算法能够准确的求解出机器人的姿态信息,具有良好的有效性和通用性。     

腿式移动着陆器的运动学建模和运动规划

着陆器是深空软着陆探测的核心装备,但现有着陆器不具备行走移位功能,一次发射任务探测范围有限。针对上述问题,该文研究了一种集着陆和行走移位功能于一体的腿式移动着陆器,建立腿式移动着陆器单腿的完整运动学模型,并阐述其工作模式。针对星体表面的复杂环境,提出一种周期步态和自由步态的规划方法,解决了稳定判据、落足点评价函数和足端轨迹规划等问题。此外,该文还通过仿真实验,验证了该方法的可行性和稳定性。     

Dynamic Motion Planning for Mobile Robots Using Potential Field Method

The potential field method is widely used for autonomous mobile robot path planning due to its elegant mathematical analysis and simplicity. However, most researches have been focused on solving the motion planning problem in a stationary environment where both targets and obstacles are stationary. This paper proposes a new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving. Firstly, the new potential function and the corresponding virtual force are defined. Then, the problem of local minima is discussed. Finally, extensive computer simulations and hardware experiments are carried out to demonstrate the effectiveness of the dynamic motion planning schemes based on the new potential field method.     

Gait optimization of step climbing for a hexapod robot

RHex-style hexapod robot is a type of legged robot which can perform multiple moving gaits according to different applications, due to its simple structure and strong mobility. However, traversing high obstacles has always been a big challenge for legged robots. In this paper, gait optimization of a hexapod robot is proposed for climbing steps at different heights, which even enables the robot to climb the step 3.9 times of the leg length. First, a previous step-climbing gait is optimized by adjusting body inclination when placing front legs on top of the step, which enables RHex with different sizes to perform the rising stage of the gait. Second, to improve the climbing heights, a novel quasi-static climbing gait is proposed by using the reversed claw-shape legs to reach the higher step. The nondeformable legs are used to raise the center of mass (COM) of the body by lifting the front and rear legs alternately so that the front legs can reach the top of the step, then the front and middle legs are lifted alternately to maneuver COM up onto the step. The simulations and dynamic analysis of climbing steps are utilized to verify the feasibility of the improved gait. Finally, the step-climbing experiments at different heights are performed with the optimized gaits to compare with the existing gaits. The results of simulations and experiments show the superiority of the proposed gaits due to climbing higher steps.     

Including Joint Torques and Power Consumption in the Stability Margin of Walking Robots

Walking robots possess important inherent advantages as autonomous systems, and many techniques have been developed during the last three decades to improve these mobile systems significantly. However, when robots attempt to walk through realistic scenarios, some techniques exhibit important shortcomings. One such shortcoming is to define the robot's quasi-static-stability margin using only the geometric parameters of the robot, neglecting the influence of real systems' motor-torque and power-consumption limitations. This paper reviews quasi-static stability theory for walking robots, illustrates real problems through simulation and experiments using real walking machines, and proposes a new concept of quasi-static stability that takes into consideration some of the robot's intrinsic parameters. The resulting stability measurement can improve efficiency in terms of robot design and power consumption, two aspects that are of paramount importance in autonomous walking robots for real applications.     

蛇形机器人步态产生及步态分析

以简化的Serpenoid曲线为基础,并根据蛇形机器人的3维运动由其水平和怪直两个平面的运动合成的理论,提出了一种蛇形机器人的3维步态产生方法.通过实验验证了各种步态,并在实验中得到了蛇形机器人各种步态的运动特性与相应的运动控制方程参数之间的关系.在实验中,得到了一种新步态,并将其命名为螺旋步态.对于螺旋步态,利用运动...     

Adaptive Dynamic Clustered Particle Filtering for Mobile Robots Global Localization

This article presents an adaptive dynamic clustered particle filtering method for mobile robot global localization. The posterior distribution of robot pose in global localization is usually multimodal due to the symmetry of the environment and ambiguous detected features. Moreover, the multimodal distribution of the posterior varies as the robot moves and observations be obtained. Considering these characteristics, we use a set of clusters of particles to represent the posterior. These clusters are dynamically evolved corresponding to the varying posterior by merging the overlapping clusters and splitting the diffuse clusters or those whose particles gather to some sub-clusters inside. Further, in order to improve computational efficiency without sacrificing estimation accuracy, a mechanism for adapting the sample size of clusters is proposed. The theoretical lower bound of the number of particles needed to limit the estimation error is derived, based on the central limit theorem in multi-dimensional space and the statistic theory of Importance Sampling. Then, a method for tuning the sample size for each cluster according to the derived lower bound is presented. Experiment results show the effectiveness of the proposed method, which is sufficient to achieve robust tracking of robot’s real pose and meanwhile significantly enhance the computational efficiency.     

一种持续规划系统在四足机器人足球中的应用

四足机器人足球赛是一个典型的动态不确定环境。论文以四足机器人足球为背景和平台,对一种新的持续规划系统POMDPRS进行了分析和改进,并将改进后的系统应用到实际的比赛中。改进后的系统减小了时间消耗,与传统的反应式系统相比,对环境的动态不确定性表现出更好的适应性。     

动态环境中移动机器人地图构建的研究进展

大部分现有的移动机器人地图构建方法都是基于静态环境的假设,而实际应用中移动机器人的工作环境是随时间变化的.综述了动态环境中移动机器人地图构建的最新研究进展,介绍了基于地图、基于运动和基于跟踪的检测动态障碍物的各种方法,分析比较了动态环境中移动机器人过滤运动障碍物传感器观测信息和结合运动障碍物传感器观测信息构建环境地图的主要方法,并总结了各种方法的优缺点.探讨了动态环境中移动机器人地图构建存在的难点问题,并展望了该领域的研究方向.     

Hybrid Dynamic Control Algorithm for Humanoid Robots Based on Reinforcement Learning

In this paper, hybrid integrated dynamic control algorithm for humanoid locomotion mechanism is presented. The proposed structure of controller involves two feedback loops: model-based dynamic controller including impart-force controller and reinforcement learning feedback controller around zero-moment point. The proposed new reinforcement learning algorithm is based on modified version of actor-critic architecture for dynamic reactive compensation. Simulation experiments were carried out in order to validate the proposed control approach.The obtained simulation results served as the basis for a critical evaluation of the controller performance.     

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.     

面向仿人机器人自然步态规划的人体步行实验分析

自然步态规划方法是实现仿人机器人步态柔顺和能量优化的可行方法,该方法要求对人体步行及其平衡策略进行定量研究．本文分析自然步态规划方法的原理,建立了一套快捷有效的人体步态测试系统,并通过实验建立了人体步行的参数化数据库．实验结果揭示了人体步行的参数化特征及其平衡策略,对于仿人机器人的自然步态规划及控制提供了理论指导．结论特别指出,仅仅通过规划的方式实现仿人机器人的自然步态是不完备的,自然步态的实现必须同仿生控制策略相结合．同时实验结论对于仿人机器人的本体优化设计也提供了参考．     

基于主支撑腿运动优化的仿人机器人快速步态规划算法

提出一种基于主支撑腿运动优化的快速步态规划算法,利用快速动态步行的特点,规划ZMP(Zero Moment Point)适时地离开质心投影并始终停留在稳定的支撑区域内．规划过程中考虑了仿人机器人摆动足触地时的碰撞,整个步态产生于深度的优化过程．     

A Navigation System for Cleaning Robots

Free navigation in indoor environments is one of the main enabling technologies for many service robot applications. The SIEMENS navigation system SINAS which is primarily targeted towards cleaning robot applications, has proved its suitability for tough everyday operation since August 1996 on several occasions, e.g., in several chain store supermarkets. This paper discusses the main requirements of a navigation system for cleaning robots, presents the architecture and main modules of the SINAS system, and reports on real-world experiences.     

动态双足机器人的控制与优化研究进展

对动态双足机器人的可控周期步态的稳定性、鲁棒性和优化控制策略的国内外研究现状与发展趋势进行了探讨.首先,介绍动态双足机器人的动力学数学模型,进一步,提出动态双足机器人运动步态和控制系统原理;其次,讨论动态双足机器人可控周期步态稳定性现有的研究方法,分析这些方法中存在的缺点与不足;再次,研究动态双足机器人的可控周期步态优化控制策略,阐明各种策略的优缺点;最后,给出动态双足机器人研究领域的难点问题和未来工作,展望动态双足机器人可控周期步态与鲁棒稳定性及其应用的研究思路.     

General Solution for the Dynamic Modeling of Parallel Robots

In this paper, we present a general method to calculate the inverse and direct dynamic models of parallel robots. The models are expressed in a closed form by a single equation in which all the elements needed are expressed. The solution is given in terms of the dynamic models of the legs, the dynamics of the platform and some Jacobian matrices. The proposed method is applied in this paper on two parallel robots with different structures. Categories (2), (3).