A General Framework for Planning Landmark-Based Motions for Mobile Robots

In this paper, we present a novel generic approach for planning landmark-based motion. The method consists in selecting automatically the most relevant landmarks along a preplanned geometric path. It proposes a strategy to correct the trajectory and to smoothly switch among the landmarks of the environment. Experimental results highlight the relevance of the proposed formalism.     

Motion Planning Strategy for Finding an Object with a Mobile Manipulator in Three-Dimensional Environments

In this paper, we investigate the problem of minimizing the average time required to find an object in a known three-dimensional environment. We consider a 7-d.o.f. mobile manipulator with an 'eye-in-hand' sensor. In particular, we address the problem of searching for an object whose unknown location is characterized by a known probability density function. We present a discrete formulation, in which we use a visibility-based decomposition of the environment. We introduce a sample-based convex cover to estimate the size and shape of visibility regions in three dimensions. The resulting convex regions are exploited to generate trajectories that make a compromise between moving the manipulator base and moving the robotic arm. We also propose a practical method to approximate the visibility region in three dimensions of a sensor limited in both range and field of view. The quality and success of the generated paths depend significantly on the sensing robot capabilities. In this paper, we generate searching plans for a mobile manipulator equipped with a sensor limited in both field of view and range. We have implemented the algorithm and present simulation results.     

Coordination of Multiple Control Schemes for Mobile Robot Navigation on the Basis of the Generalized Stochastic Petri-Nets

There have been two major streams of research for the motion control of mobile robots: model-based deliberate control and sensor-based reactive control. Since the two schemes have complementary advantages and disadvantages, each cannot completely replace the other. There are a variety of environmental conditions that affect the performance of navigation. The motivation of this study is that multiple motion control schemes are required to survive in dynamic real environments. In this paper, we exploit two discrete motion controllers for mobile robots. One is the deliberate trajectory tracking controller and the other is the reactive dynamic window approach. We propose the selective coordination of two controllers on the basis of the generalized stochastic Petri net (GSPN) framework. The major scope of this paper is to clarify the advantage of the proposed controller based on the coordination of multiple controllers from the results of quantitative performance comparison among motion controllers. For quantitative comparison, both simulations and experiments in dynamic environments were carried out. In addition, it is shown that navigation experiences are accumulated in the GSPN formalism. The performance of navigation service can be significantly improved owing to the automatically stored experiences.     

基于改进梯度投影算法的移动机械臂轨迹规划研究

移动机械臂由移动平台和机械臂构成,是一种典型的冗余机械臂系统。其运动学和轨迹规划问题是研究热点。梯度投影法是求解该问题的一类常用算法,其应用难点主要集中在比例因子的选取上。极值法通过最优化方法求解比例因子,将比例因子作为目标函数,并基于关节速度极限、可优化度等设计约束条件。针对极值法存在使关节加速度超限的问题,提出一种考虑关节加速度约束的新算法,并通过仿真对比验证该算法的有效性。     

Error Analysis and Effective Adjustment of the Walking-Ready Posture for a Biped Humanoid Robot

A walking control algorithm is generally a mixture of various controllers; it depends on the characteristics of the target system. Simply adopting one part of another researcher's algorithm does not guarantee an improvement in walking performance. However, this paper proposes an effective algorithm that can be easily adopted to other biped humanoid robots; the algorithm enhances the walking performance and stability of the robot merely by adjusting the walking-ready posture. The walking performance of biped humanoid robots is easily affected by an unsuitable walking-ready posture in terms of accuracy and repeatability. More specifically, low accuracy for the walking-ready posture may cause a large difference between an actual biped robot and its mathematical model, and the low repeatability may disturb the evaluation of the performances of balance controllers. Therefore, this paper first discusses the factors that detrimentally affect bipedal walking performance and their phenomena in the walking-ready posture. The necessary conditions for an ideal walking-ready posture are then defined based on static equilibrium and a suitable adjustment algorithm is proposed. Finally, the effectiveness of the algorithm is verified through dynamic computer simulations.     

基于网格法的机械臂无碰撞轨迹规划

介绍了高压带电作业机械臂在三维空间中进行无碰撞轨迹规划的一种方法,通过对整个作业空间进行网格化划分,完整的描述出自由空间与障碍物空间,并对每一个网格进行索引对应,使其在利用 A＊算法搜索路径是可以迅速准确的得到最优的无碰撞路径,减少系统的运行时间。     

基于激光雷达的移动机器人实时位姿估计方法研究

位姿估计是移动机器人研究中的一个关键问题,对于运动目标跟踪、机器人导航、地图 生成等具有重要意义,提出了一种基于二维激光雷达的实时位姿估计方法,包括基于Hough变 换的切线角度直方图算法和迭代切线加权最近点算法两部分.两种算法的结合和切线信息的引 入.有效地解决了传统方法无法解决的局部最小值、类孔径、大计算量等问题.仿真数据和室外 环境实际数据的大量实验结果表明它具有精度高、速度快、适用性广和对噪声、遮挡和类孔径问 题鲁棒性高的特点.     

基于多传感器的移动机器人路径规划

提出一种基于多传感器的移动机器人路径规划策略。利用声纳传感器和CCD摄像机对环境进行探测,得到关于障碍物的信息,通过一种简单、快速的数据融合算法计算出障碍物相对于机器人的位置坐标。采用切线法进行路径规划,实现了移动机器人在不确定环境下的路径规划,使机器人可以很好地避开障碍物,并以局部最优或次最优路径到达指定位置。实验结果验证了该路径规划算法的良好性能。     

基于雅可比转秩-RRT法的冗余机械手路径规划

针对核反应堆检修用机械手在末端任务给定的无碰撞路径规划问题进行研究.提出一种将雅可比转秩控制算法与快速搜索随机树法相结合的混合算法,通过选择距目标点工作空间距离最近的位姿点作为树的扩充节点,避免对逆运动学进行求解.利用雅可比转秩控制算法计算出最优扩充方向,采用二分梯度下降扩充方法对末端工具速度加以限制,避免关节速度发生突变.仿真结果表明该混合算法的快速性和有效性.     

单灰度图像中眼睛定位的人脸位置矫正算法

人脸位置的矫正作为人脸检测定位的一个环节，在计算机人脸识别中具有重要的意义。本文提出了一种基于单人脸灰度图像中眼睛定位的人脸位置矫正方法，用居中度使图像小块居中，用匹配度求取适些小图像块中的两块眼睛的小块，再在小范围内对鼻子、嘴巴部分进行水平灰度投影，然后进行扶正。实验结果表明，该方法对于双眼可见单人脸灰度图像能实现快速有效矫正，并能在矫正结果中精确给出双眼瞳孔位置。     

基于深度学习初始位姿估计的机器人摄影测量视点规划

针对机器人摄影测量中离线规划受初始位姿标定影响的问题, 提出融合初始位姿估计的机器人摄影测量系统视点规划方法. 首先构建基于YOLO (You only look once) 的深度学习网络估计被测对象3D包围盒, 利用PNP (Perspective-N-point)算法快速求解对象姿态; 然后随机生成机器人无奇异无碰撞的视点, 基于相机成像的2D-3D正逆性映射, 根据深度原则计算每个视角下目标可见性矩阵; 最后, 引入熵权法, 以最小化重建信息熵为目标建立优化模型, 并基于旅行商问题(Travelling saleman problem, TSP)模型规划机器人路径. 结果表明, 利用深度学习估计的平移误差低于5 mm, 角度误差低于2°. 考虑熵权的视点规划方法提高了摄影测量质量, 融合深度学习初始姿态的摄影测量系统提高了重建效率. 利用本算法对典型零件进行摄影测量质量和效率的验证, 均获得优异的位姿估计和重建效果. 提出的算法适用于实际工程应用, 尤其是快速稀疏摄影重建, 促进了工业摄影测量速度与自动化程度提升.     

基于神经网络的移动机器人路径规划

针对移动机器人未知环境下的安全路径规划,本文采用了一种局部连接Hopfield神经网络（ANN）规划器。对任意形状环境,ANN中兼顾处理了“过近”和“过远”来形成安全 路径,而无需学习过程。为在单处理器上进行有效的在线路径规划,提出用基于距离变换的串行模拟,加速数值势场的传播。仿真表明,该方法具有较高的实时性和环境适应性。     

基于免疫进化的移动机器人路径规划

针对现有基于进化算法在路径规划中的易陷入局部最优和缺乏指导性的缺点,该文探讨了一种基于免疫进化的路径规划方法;该方法针对机器人路径规划的实际应用,优化了变异算子,引入了免疫机制,使得较优个体能较早地生成,保证了算法的收敛速度,同时在算法过程中保持了种群的多样性,防止了早熟收敛,提高了全局搜索能力;仿真结果表明,该方法对复杂地图有良好的适应能力,能有效地保证路径的规划效率并改善路径规划的质量。     

基于改进人工势场法的机械手避障规划

针对三维环境中机械手在障碍物附近目标不可达问题和局部最小值问题,提出一种基于改进人工势场法的机械手避障方法.该方法以机械手末端所受合力的方向作为其运动方向,通过势场力的作用使机械手末端避开障碍物,解决障碍物附近目标不可达问题;采用X-Y平面内的角度偏移法,使机械手末端迅速跳出局部最小值,解决势场法的局部最小值问题;从而使机械手避开障碍物到达目标位置,并给出了机械手避障规划算法的具体实现步骤.将该方法应用于机械手末端位置、障碍物位置和目标位置已知条件下的常规作业任务中,仿真实验结果表明,机械手末端沿着规划路径可跳出局部最小值,并避开障碍物,成功到达目标位置,验证了该算法的有效性.     

移动机器人路径规划方法研究

针对室内动态非结构化环境下的移动机器人路径规划问题,提出了一种能够将全局路径规划方法和局部路径规划方法相结合、将基于反应的行为规划和基于慎思的行为规划相结合的路径规划方法．全局路径规划器采用A*算法生成到达目标点的子目标节点序列;局部路径规划器采用改进的人工势场方法对子目标节点序列中相邻两节点进行路径平滑和优化处理．在考虑了移动机器人运动学约束的前提下,该方法不但能够充分利用已知环境信息生成全局最优路径,而且还能及时处理所遇到的随机障碍信息．仿真研究与在室内复杂环境下的实际运行结果验证了该方法的有效性．     

基于Kinect的移动机器人实时局部路径规划

传统路径规划方法计算复杂、效率低,且误差较高.为此,提出一种基于Kinect的移动机器人实时局部路径规划方法.利用Kinect产生的RGB图像和3D图像实时获取移动机器人的周边动态环境信息,通过模糊逻辑和信息融合技术完成机器人的实时路径规划,从而实现机器人的目标跟踪与导航.实验结果表明,该方法具有较好的稳定性与实时性.     

An Experimental Study on Cartesian Impedance Control for a Joint Torque-Based Manipulator

The purpose of this paper is to present our results on experimental investigations on Cartesian impedance control and nonlinearity compensation for our harmonic drive robot based on joint torque sensors. The imperfection of the cubic model for harmonic drive friction is detected according to friction identification experiments. In addition, five different Cartesian impedance control schemes are considered and four of them are tested by corresponding experiments with/without friction compensation. Experimental results tell us that the force-based impedance control strategy is more suitable than the position-based strategy for the harmonic drive robot based on joint torque feedback.     

基于简单模糊逻辑的冗余度机器人动力学路径规划新方法

论文提出了基于模糊逻辑的冗余度机器人避障算法,算法中利用模糊规则自动调整避障控制参数,使机器人在最短的时间内做出快速回避反应,提高了系统的智能性;另一方面,算法中利用动力学控制代替了位置控制,减少了避障过程中,由于速度突变引起的关节冲击力,提高了系统使用寿命。最后通过一平面三连杆三自由度机器人进行仿真研究,结果证实了该算法的有效性。     

一种基于粒子群算法的移动机器人路径规划方法

针对结构化环境中移动机器人路径规划问题,提出一种基于粒子群的路径规划算法.该算法利用适应度函数描述环境约束及路径的距离信息,适应度函数通过神经网络计算;由路径节点构成粒子,通过混合粒子群算法进行寻优.最后,通过计算机仿真验证了该算法是合理的,并且可应用于机器人的实时导航.     

基于势场法的移动机器人避障路径规划

针对势场法所固有的几个缺陷,提出了一种基于势场法的移动机器人避障路径规划算法,并成功应用于未知复杂环境下移动机器人的路径规划中。仿真试验表明:提出的方法具有较强的路径规划能力,克服了传统势场法的缺点,具有较强的实用性。