仿人机器人实时路径规划方法研究

为了使仿人机器人在人类生活环境中自由行走,将仿人机器人的动作离散化为指定的动作,将状态空间离散化为网格,利用立体视觉和平面提取方法建立环境地图,将仿人机器人的轮廓简化为双圆柱模型进行避障检测,最终在环境地图中搜寻代价最小的一系列可行的动作作为路径,通过仿真实验验证了方法的有效性。     

VFF^＋：改进的虚拟力场移动机器人避障算法

分析了虚拟力场法采用全局栅格表示环境信息具有累积误差大、信息存储量大的缺点，设计了动态栅格法表示环境信息，使用跟随机器人移动的扇形栅格表示环境信息，使用栅格中心坐标投影的方法存储多次超声测量数据信息，与势场法相结合对机器人进行导航控制。经仿真和实验验证，改进后的虚拟力场法取得了良好的应用效果。     

Webots平台的仿人机器人仿真的研究

仿人机器人是机器人研究领域的热点,可以应用于工业、医疗和家庭服务等领域。机器人仿真技术可以帮助研究者更好地研究机器人的结构和运动控制。本文基于Webots软件,构建HOAP2机器人的运动仿真平台,详细说明了机器人仿真环境的构建过程以及运动控制的仿真过程。仿真结果说明,本研究构建的仿真平台是有效的。     

仿人机器人概述

１引言现阶段 ,机器人的研究应用领域不断拓宽 ,其中仿人机器人的研究和应用尤其受到普遍关注 ,并成为智能机器人领域中最活跃的研究热点之一。研制与人类外观特征类似 ,具有人类智能、灵活性 ,并能够与人交流 ,不断适应环境的仿人机器人一直是人类的梦想之一。世界上最早的仿人机器人研究组织诞生于日本 ,１９７３年 ,以早稻田大学加藤一郎教授为首 ,组成了大学和企业之间的联合研究组织 ,其目的就是研究仿人机器人。加藤一郎教授突破了仿人机器人研究中最关键的一步———两足步行。１９９６年１１月 ,本田公司研制出了自己的第一台仿人步…     

仿人机器人在复杂环境中的行走研究

在仿人机器人行走限定性的研究中,由于外界环境的复杂性,仿人机器人在行走过程中很容易失稳,导致不能稳定行走的问题.为了避免失稳摔倒,结合FZMP的在线调整策略,提出了通过调整直立姿态、调整落地角动量控制、落地减振控制和落地位置控制四种稳定行走控制方法,通过改变髋关节的高度来吸收由摆动腿提前着地而产生的垂直振动,给出了髋关节的高度补偿计算公式.使得机器人行走的整个过程,特别是在地面不平整以及摆动腿落地瞬间冲击力较大时也能保持良好的稳定性.通过ADAMS软件和虚拟仿真验证,改进方法能有效的实现机器人在复杂环境中的稳定行走.     

足球反作用力下仿人机器人姿态控制研究

本文以仿人机器人踢足球为例,以现实机器人为原型,利用Solidworks建立了仿人机器人的三维机械结构模型,利用ADAMS和Simulink联合仿真的方法,仿真得到了机器人踢足球的整个过程,利用ZMP理论实时求得机器人的重心轨迹,计算与理想轨迹的偏差,通过改变机器人姿态以减小偏差,实现了对机器人的闭环控制,提高了机器人在受外力作用下的稳定性,并进行了实物实验,验证了该方法的有效性。     

仿人机器人的研究历史、现状及展望

仿人机器人是当前机器人研究领域最活跃的研究方向之一，引起了许多科研工作者的 注意．本文介绍了仿人机器人与其他移动机器人相比的主要优点，对国内外仿人机器人的研 制工作作了综述，并对将来的研究方向和工作重点作出了展望．     

仿人机器人柔性腰部机构研究

仿人机器人腰部的构成对仿人机器人的运动学、动力学性能起着重要的作用．本 文着重分析了目前仿人机器人腰部机构存在的问题，提出了一种具有柔性特征的仿人机器人 腰部设计方案，并分析了此腰部机构对机器人的运动稳定性、操作柔顺性的影响．本设计使 仿人机器人具有良好的柔顺性，提高了机器人与人协作时的安全性、稳定性和抗干扰能力．     

室内清洁机器人避障路径规划研究

针对室内清洁机器人尽可能充满室内的可达区域执行清扫任务的需求，提出一种基于传感信息的清洁机器人的路径规划算法。在室内清扫环境未知的情况下，这种算法比较简单，清扫的效率较高。清洁机器人位姿也易于控制，且具有自主避障的功能。     

智能仿人机器人的现状及展望

仿人机器人是当前智能机器人研究领域中最新的研究方向之一,并引起了广泛的注意。本文介绍了作为智能机器人重要表现形式的仿人机器人的特点,对世界上针对仿人机器人的研究工作进行了综述,指出了各自的侧重点及不足之处,指出了今后研究工作的重点。     

Modeling and multiobjective optimization of traction performance for autonomous wheeled mobile robot in rough terrain

Application of terrain-vehicle mechanics for determination and prediction of mobility performance of autonomous wheeled mobile robot(AWMR) in rough terrain is a new research area currently receiving much attention for both terrestrial and planetary missions due to its significant role in design,evaluation,optimization,and motion control of AWMRs.In this paper,decoupled closed form terramechanics considering important wheel-terrain parameters is applied to model and predict traction.Numerical analysis of traction performance in terms of drawbar pull,tractive efficiency,and driving torque is carried out for wheels of different radii,widths,and lug heights,under different wheel slips.Effects of normal forces on wheels are analyzed.Results presented in figures are discussed and used to draw some conclusions.Furthermore,a multiobjective optimization(MOO) method for achieving optimal mobility is presented.The MOO problem is formulated based on five independent variables including wheel radius r,width b,lug height h,wheel slip s,and wheel rotation angle θ with three objectives to maximize drawbar pull and tractive efficiency while minimizing the dynamic traction ratio.Genetic algorithm in MATLAB is used to obtain optimized wheel design and traction control parameters such as drawbar pull,tractive efficiency,and dynamic traction ratio required for good mobility performance.Comparison of MOO results with experimental results shows a good agreement.A method to apply the MOO results for online traction and mobility prediction and control is discussed.     

Navigation system for an autonomous robot using an ocellus camera in an indoor environment

Autonomous and mobile robots are being expected to provide various services in human living environments. However, many problems remain to be solved in the development of autonomous robots that can work like humans. When a robot moves, it is important that it be able to have self-localization abilities and recognize obstacles. For a human, the present location can be correctly checked through a comparison between memorized information assuming, it is correct, and the present situation. In addition, the distance to an object and the perception of its size can be estimated by a sense of distance based on memory or experience. Therefore, the environment for robotic activity assumed in this study was a finite-space such as a family room, an office, or a hospital room. Because an accurate estimation of position is important to the success of a robot, we have developed a navigation system with self-localization ability which uses only a CCD camera that can detect whether the robot is moving accurately in a room or corridor. This article describes how this system has been implemented and tested with our developed robot.     

The use of force feedback and auditory cues for performance of an assembly task in an immersive virtual environment

Using an immersive virtual environment, this study investigated whether the inclusion of force feedback or auditory cues improved manipulation performance and subjective reports of usability for an assembly task. Twenty-four volunteers (12 males and 12 females) were required to assemble and then disassemble five interconnecting virtual parts with either auditory, force, or no feedback cues provided. Performance for the assembly task was measured using completion time and number of collisions between parts, while the users preferences across conditions were evaluated using subjective reports of usability. The results indicated that the addition of force feedback slowed completion time and led to more collisions between parts for males. In contrast, females exhibited no change in the mean completion time for the assembly task but did show an increase in collision counts. Despite these negative performance findings when adding force feedback, users did report perceived increases in realism, helpfulness and utility towards the assembly task when force feedback was provided. Unlike force feedback, the results showed that auditory feedback, indicating that parts had collided during the assembly task, had no negative performance effects on the objective measures while still increasing perceived realism and overall user satisfaction. When auditory cues and force feedback were presented together, performance times, number of collisions, and usability were not improved compared to conditions containing just auditory cues or force feedback alone. Based on these results, and given the task and display devices used in the present study, the less costly option of excluding auditory and force feedback cues would produce the best performance when measured by the number of collisions and completion time. However, if increased ratings of usability for an assembly task are desired while maintaining objective performance levels and reduced cost, then the inclusion of auditory feedback cues is best.     

Type-2 fuzzy control for a flexible-joint robot using voltage control strategy

Type-1 fuzzy sets cannot fully handle the uncertainties. To overcome the problem, type-2 fuzzy sets have been proposed. The novelty of this paper is using interval type-2 fuzzy logic controller (IT2FLC) to control a flexible-joint robot with voltage control strategy. In order to take into account the whole robotic system including the dynamics of actuators and the robot manipulator, the voltages of motors are used as inputs of the system. To highlight the capabilities of the control system, a flexible joint robot which is highly nonlinear, heavily coupled and uncertain is used. In addition, to improve the control performance, the parameters of the primary membership functions of IT2FLC are optimized using particle swarm optimization (PSO). A comparative study between the proposed IT2FLC and type-1 fuzzy logic controller (T1FLC) is presented to better assess their respective performance in presence of external disturbance and unmodelled dynamics. Stability analysis is presented and the effectiveness of the proposed control approach is demonstrated by simulations using a two-link flexible-joint robot driven by permanent magnet direct current motors. Simulation results show the superiority of the IT2FLC over the T1FLC in terms of accuracy, robustness and interpretability.     

未知环境下移动机器人实时路径规划

针对在未知环境下实现移动机器人实时的路径规划问题,提出了一种将快速扩展随机树（RRT）算法与视野域自适应的滚动窗口相结合的路径规划算法。该方法实时获取滚动窗口内的局部环境信息,根据环境的变化,滚动窗口视野域进行自适应调整,通过分析滚动窗口内传感器获取的信息,结合改进后的RRT算法筛选出可行的路径,控制移动机器人到达子目标点,在此过程中动态监测规划好的路径,确保路径合理,并重复上述过程,直至到达目标区域。实验对比分析表明,该方法能实时并有效实现未知环境下移动机器人的路径规划。     

A system for self-diagnosis of an autonomous mobile robot using an internal state sensory system: fault detection and coping with the internal condition

Considering that intelligent robotic systems work in a real environment, it is important that they themselves have the ability to determine their own internal conditions. Therefore, we consider it necessary to pay some attention to the diagnosis of such intelligent systems and to construct a system for the self-diagnosis of an autonomous mobile robot. Autonomous mobile systems must have a self-contained diagnostic system and therefore there are restrictions to building such a system on a mobile robot. In this paper, we describe an internal state sensory system and a method for diagnosing conditions in an autonomous mobile robot. The prototype of our internal sensory system consists of voltage sensors, current sensors and encoders. We show experimental results of the diagnosis using an omnidirectional mobile robot and the developed system. Also, we propose a method that is able to cope with the internal condition using internal sensory information. We focus on the functional units in a single robot system and also examine a method in which the faulty condition is categorized into three levels. The measures taken to cope with the faulty condition are set for each level to enable the robot to continue to execute the task. We show experimental results using an omnidirectional mobile robot with a self-diagnosis system and our proposed method.     

An output feedback parallel force/position regulator for a robot manipulator in contact with a compliant environment

In this paper the problem of regulating force and position for a robot manipulator in contact with an elastically compliant environment is considered. In the framework of parallel force/position control, an output feedback regulator with gravity compensation and desired force feedforward is proposed which only requires measurements of force and position. Semiglobal stability of the closed-loop system around the equilibrium is shown via a Lyapunov argument.     

Region with velocity constraints: map information and its usage for safe motion planning of a mobile robot in a public environment

Recently, various autonomous mobile robots have been developed for practical use. To support the coexistence of robots and humans in real environments, we propose a concept named ‘Region with Velocity Constraints (RVC),’ which is set around hazardous areas. RVCs are regions where the velocities of the robot are constrained to predefined values. Inside the RVCs, the robot has to reduce its translational velocity to avoid predicted hazards such as collisions with obstacles, and to reduce its rotational velocity to prevent undesirable motions such as sharp turns. We also propose a motion planning method for navigating the mobile robot in an environment with RVCs based on the Navigation Function and Global Dynamic Window Approach. Our method generates a trajectory satisfying both translational and rotational velocity constraints to be compatible with the surroundings. Moreover, to demonstrate the validity of our method, we performed numerical simulations and experiments.     

Generation of an optimal architecture of neuro force controllers for robot manipulators in unknown environments using genetic programming with fuzzy fitness evaluation

 In this paper, we have applied genetic programming to generate an optimal architecture of neuro force controllers for robot manipulators in any environment. In order to perform precise force control in unknown environments, the optimal structured neuro force controller is generated using genetic programming with fuzzy fitness evaluation. After the architecture of the neuro controller has been optimized for any kinds of environments, it can be applied for a robot contact task with an unknown environment in on-line manner using its own adaptation ability. An effective crossover operation is proposed for the efficient evolution of the controllers. The simulation has been carried out to evaluate the effectiveness of the proposed robot force controller.