Insectomorphic robot climbing a freely rolling ball

The problem of control of autonomous motion of a six-legged robot from a support horizontal plane to a ball that can freely move on this plane in an arbitrary direction is solved. Further robot motion aimed at acceleration or deceleration of the ball both in the direction of the longitudinal axis of its body and in the transverse direction ensuring dynamic stability of the robot on the ball is synthesized. Analytical conditions of implementability of the maneuver of climbing a ball are found. Formulas for estimating the maximum ball radius for which climbing of the robot is possible are obtained. Using the developed control algorithms, the robot can climb the ball and, staying on it, move the ball to the desired position in the plane. Robot motion is performed owing to the dry friction forces. Asymptotic stability of the programmed motion of the whole system is provided by a PD controller, which implements necessary step cycles of legs motion and the planned law of body motion. Results of 3D computer simulation of the controlled robot dynamics are discussed.     

An insectomorphic robot climbing over a freely rolling ball

An algorithm for the control of an insectomorphic robot climbing over a ball that rolls freely on a horizontal plane is developed and tested using computer simulation. The proposed motion involves three maneuvers. First, the robot climbs the ball at rest from the horizontal surface. At the end of this maneuver, the ball gains an angular velocity due to errors in the execution of the programmed motion. The further motion of the robot is designed so as to reduce the velocity gained in the course of climbing to an acceptable level. The motion is completed by the maneuver of getting down to the supporting horizontal plane from the almost motionless ball. The robot motion is implemented using the Coulomb friction without any special devices. The asymptotic stability of the programmed motion of the system as a whole is ensured by a PD controller that implements the step cycles of the leg motions and the planned motion of the body. Results of 3D computer simulation of the robot motion are discussed. The model of the mechanical robot-ball system is formed using the Universal Mechanism program package; this model is described by an automatically derived system of differential equations that take into account the dynamics of all solid elements.     

Biologically inspired tree‐climbing robot with continuum maneuvering mechanism

Treebot is the first tree‐climbing robot that is capable of climbing from a tree trunk to a branch. The robot employs several design principles adapted from arboreal animals, including claw gripping and inchworm locomotion, with a certain artificial optimization to achieve high maneuverability on irregular‐shaped trees. Treebot is composed of a pair of tree grippers that permits Treebot to attach to a wide variety of trees with a wide range of gripping curvature, and a novel continuum maneuvering structure that provides high maneuverability and adaptability. In the robot actuation, only five actuators are necessary. Although Treebot weighs only 600 gr, it has a payload capability of 1.75 kg, which is nearly three times its own weight. This paper describes the design process and specifically addresses the robot locomotion and optimization of gripping force. Experimental results demonstrate the robot's ability to climb trees with high maneuverability. © 2012 Wiley Periodicals, Inc.     

Maneuvering control of a rolling four-links robot

This work deals with the maneuvering control of the planar motion of a rolling four-links robot as described in Figure 1. The system is composed of four links, two identical wheels, and a mass m_O attached to the joint O. The problem that is addressed is to develop control laws for the rolling four-links robot such that the mass m_O performs prescribed maneuvers in the vertical (X, Z)-plane.     

Shipping Cargo on a Raft by an Insectomorphic Robot

An algorithm for designing the motion of a hexapod robot aimed at shipping the robot together with a cargo to the other shore of a body of water on a raft in the simple case when the robot imparts the initial push to the raft from the shore is described. The proposed motion control algorithm includes transporting the cargo from the shore to the raft, moving the cargo across the moving raft, and carrying the cargo from the raft to the other shore. The algorithm is worked out using computer simulation within the complete dynamical model of motion taking into account the nonstationary action of water on the raft. The numerical results prove the validity of the algorithm as long as sufficient data about the motion for the purpose of control is available.     

Sub-optimality analysis of mobile robot rolling path planning

Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.     

一种改进的机器人滚动路径规划算法

针对静态和动态障碍物共存环境中机器人滚动路径规划的鲁棒性问题,提出了通过确定局部子目标位置判断机器人行进路线的路径规划算法.机器人以滚动窗口的形式实时检测局部环境信息,寻找并确定局部子目标的位置,从而做出下一步安全路径规划.机器人不断重复该过程,最终沿着一条优化路径安全到达目标点.仿真结果表明:该算法能使机器人沿着优化...     

Velocity control of a cylindrical rolling robot by shape changing

A rolling robot is developed that possesses an elliptically shaped outer surface with the ability to change shape as it rolls, resulting in a gravity-powered torque imbalance that accelerates or brakes the robot’s motion. Angular position and velocity are measured onboard and used as feedback control to trigger and define shape change actuation. Goal of the control is to direct the robot to follow a given step angular velocity profile. An equation of motion for the rolling robot is derived and solved numerically, and simulations are compared to velocity data from roll trials of the actual robot. Results show that when the robot is given a set of advantageous initial conditions, it is able to accelerate from rest, maintain constant average velocity, and brake its motion in order to follow a desired velocity profile with significant accuracy.     

未知环境下基于有先验知识的滚动Q学习机器人路径规划

提出一种未知环境下基于有先验知识的滚动Q学习机器人路径规划算法.该算法在对Q值初始化时加入对环境的先验知识作为搜索启发信息,以避免学习初期的盲目性,可以提高收敛速度.同时,以滚动学习的方法解决大规模环境下机器人视野域范围有限以及因Q学习的状态空间增大而产生的维数灾难等问题.仿真实验结果表明,应用该算法,机器人可在复杂的未知环境中快速地规划出一条从起点到终点的优化避障路径,效果令人满意.     

利用机器人行为动力学与滚动窗口路径规划

针对存在静态障碍物的未知环境下移动机器人路径规划问题,提出运用行为动力学与滚动窗口相结合进行路径规划的方法。首先根据所获得的窗口（局部环境）信息,采用启发式函数进行局部子目标优化选择;然后将路径规划问题即导航行为分解为趋于目标行为和避障行为,并对这两种行为分别建立了行为状态和行为模式动力学模型;在此基础上,以窗口为单位,利用导航行为动力学模型进行在线自主路径规划;将一系列窗口中的规划轨迹按照连续性条件首尾相接,最终完成了一条全局规划任务。该方法原理简单,计算量小,规划路径光滑,具有较强的实际应用价值。通过计算机实例仿真验证了该方法的有效性和适应性。     

Online trajectory planning of robot arms for interception of fast maneuvering object under torque and velocity constraints

This paper presents a novel approach to an online trajectory planning of robot arms for the interception of a fast-maneuvering object under torque and velocity constraints. A body axis is newly introduced as a trajectory-planning coordinate in order to meet the position and the velocity matching conditions for a smooth grasp of the fast-maneuvering object. Using the position of the object and the end-effector in the inertia axis, the acceleration commands are generated in the X-, Y-, and Z-directions of the body axis and the acceleration commands are modified considering the torque and the velocity constraints. The trajectory planning in the X-direction becomes the speed planning to achieve the maximum speed, whereas the trajectory planning in the Y- and Z-directions becomes the direction planning where a missile-guidance algorithm is employed to intercept the maneuvering object. Finally, the acceleration commands in the body axis are transformed into the angle commands of the end-effector in the joint axis, which is used as the actual trajectory commands in robot arms.     

蛇形机器人在缆索检测中螺旋滚动步态的研究

提出了一种检测桥梁缆索的方式,利用蛇形机器人在缆索上螺旋滚动步态的优点,检测缆索表面和内部损伤,克服传统的桥梁缆索检测方法的不足。研究了蛇形机器在缆索上螺旋滚动步态的实现,确定了螺旋滚动曲线的参数与蛇形机器人螺旋滚动姿态的关系。通过参数的调整和优化,使蛇形机器人既不会抱得过紧而损伤缆索,而降低蛇形机器人的运行速度和消耗蛇形机器人更多能量,又不会抱得太松而使蛇形机器人从缆索上滑落,而降低蛇形机器人在缆索上运动的安全性。最后通过Webots仿真软件的模拟真实环境,表明了蛇形机器人可以在桥梁缆索上实现螺旋运动,且螺旋运动可以适应不同直径的缆索,通过改变参数,可优化和调整蛇形机器人的螺旋形状,使蛇形机器人模块选择灵活、运动的安全和高效。     

自适应理论在目标跟踪中的应用

在机动目标跟踪与定位中,结合EKF和自适应理论的优点和目标跟踪的非线性特征,提出了一种非线性系统的基于“当前”统计模型的自适应扩展卡尔曼滤波算法,根据机动目标的测量信息修正加速度方差,消除随机误差和噪声的干扰,提高预测的精度。通过Monte Carlo对比仿真实验表明该算法正确有效,定位精度较高,滤波效果得到改善,同时增强了稳定性,优于一般的EKF和MVEKF算法,为机动目标精确跟踪与定位的实现提供一种新的方法。     

一种改进的强机动目标跟踪方法

为提高目标在强机动情况下的跟踪精度,更好地实现目标跟踪,在当前统计模型和卡尔曼滤波算法的基础上提出改进的目标跟踪方法。分析了当前统计模型,归纳出在目标弱机动和强机动情况下的优点及不足。进行强机动检测,以此判断目标的机动水平;将渐消因子引入卡尔曼滤波器,减少陈旧数据的影响,充分体现当前机动状态;在算法中在线辨识各项参数,并根据机动水平自适应地调整。仿真结果表明,改进的方法在弱机动时保持了当前统计模型的跟踪性能,而在强机动时拥有更高的跟踪精度。     

粒子滤波在机动飞行器轨道确定中的应用

对于机动飞行器轨道确定,由于状态误差及测量误差的分布不是高斯分布,传统的滤波方法受到了一定的限制,为了解决这个问题,本文采用"采样-重要性-采样"粒子滤波算法,在考虑只有目标位置信息而需对目标速度信息进行估计的情况,对含J2摄动项机动目标轨道信息进行确定.滤波过程中,结合交互式多模型方法,由多模型输出误差判断当前模型类型,通过当前模型的快速切换,提高滤波精度.最后给出应用此方法进行轨道确定的仿真实例.     

点云模型表面物体自由拖拽定位

为实现在点云表面自由、合理地拖动其他物体,提出了一种基于硬件深度缓冲的拖拽算法。首先在鼠标按下阶段独立渲染一次指定的点云,快照出当前屏幕中该点云的深度缓冲,接着在鼠标移动阶段利用记录的深度缓冲计算参考多边形下一个位置处的质心坐标和法向,再利用相邻两个参考多边形质心和法向建立物体运动的旋转和平移分量,从而实现物体在点云表面的拖拽。实验结果表明,利用该方法可以实时、合理地在指定点云表面自由拖动任何物体。     

基于粒子滤波的机动目标跟踪

在单机动目标跟踪中,目标的机动情况是未知的,提出的算法用粒子滤波器求加速度的估计,由Kalman滤波得到加速度的重要性概率密度函数。仿真实验结果表明,该算法可较好地跟踪目标状态（包括加速度）的变化。     

船舶航向保持中的混沌运动控制

针对船舶航行中的混沌运动控制问题,从船舶操纵运动非线性模型入手,提出了一种基于受控混沌系统Melnikov函数的矩形脉冲微扰控制方法。控制方法利用矩形脉冲对混沌系统参量进行微扰控制。通过求解混沌系统的同宿轨道,构造受控混沌系统的Melnikov函数,结合Melnikov函数简单零点出现的边界条件以数学的方法确定微扰脉冲参数的取值,避免了实施混沌控制时控制脉冲参数选择的盲目性。船舶混沌运动控制的仿真实验显示,所提方法能将系统混沌运动快速稳定至周期轨道上,且其振幅降为原混沌系统的8.5%;同时实验结果表明了所提方法在船舶混沌运动控制中的有效性。     

基于改进SOS算法的UCAV鲁棒机动决策研究

针对无人作战飞机自主空战机动决策问题,提出了一种鲁棒机动决策方法。设计了反映空战态势的鲁棒隶属函数,并基于此设计鲁棒多目标决策函数;针对动作库在机动决策中的不完备性与传统优化方法求解时效性缺陷,运用基于自适应和精英反向学习策略改进的共生生物算法,对控制量进行优化进而完成机动决策;仿真结果表明,鲁棒机动决策结果更具优势且改进算法求解具有实时性,满足机动决策需求。     

基于卷积神经网络的空中目标战术机动模式分类器设计

针对现有空中目标机动模式识别算法鲁棒性和抗噪性差的问题,提出了利用卷积神经网络直接对航迹数据进行非人工特征提取,从而实现机动模式识别的算法。针对目标机动段难以分割的现实情况,提出了滑动时间窗口的模式识别方法,并给出了基于滑动时间窗口的机动模式识别流程。对空中目标进行了航迹仿真,并进行了数据预处理,为卷积神经网络提供了合理训练样本。通过仿真实验确定了适合于机动模式识别的卷积神经网络的结构和参数,实验结果表明,构造好的卷积网络对机动模式的识别率达98.4%,并且在结合机动触发点后,对连续航迹的识别取得了良好效果。