Kinematics Modeling of an Omnidirectional Autonomous Mobile Robot with Castor Wheels

The kinematics model of an omnidirectional wheeled mobile robot （WMR） platform with 3 castor wheels was built, which includes the actuated inverse solution and the sensed forward solution. Motion simulations verify the consistency between the actuated inverse solution and the sensed forward solution. Analysis results show that the WMR possesses 3 degrees of freedom, and its motion trajectory is a straight line. The ＂pushing＂ and ＂pulling＂ motion patterns of the WMR can be generated by using different wheel orientations. It can be used in the places where the space is limited.

A Self-Position Estimation Algorithm for Multiple Mobile Robots Using Two Omnidirectional Cameras and an Accelerometer

This paper proposes a self-position estimate algorithm for the multiple mobile robots; each robot uses two omnidirectional cameras and an accelerometer. In recent years, the Great East Japan Earthquake and large-scale disasters have occurred frequently in Japan. From this, development of the searching robot which supports the rescue team to perform a relief activity at a large-scale disaster is indispensable. Then, this research has developed the searching robot group system with two or more mobile robots. In this research, the searching robot equips with two omnidirectional cameras and an accelerometer. In order to perform distance measurement using two omnidirectional cameras, each parameter of an omnidirectional camera and the position and posture between two omnidirectional cameras have to be calibrated in advance. If there are few mobile robots, the calibration time of each omnidirectional camera does not pose a problem. However, if the calibration is separately performed when using two or more robots in a disaster site, etc., it will take huge calibration time. Then, this paper proposed the algorithm which estimates a mobile robot＇s position and the parameter of the position and posture between two omnidirectional cameras simultaneously. The algorithm proposed in this paper extended Nonlinear Transformation （NLT） Method. This paper conducted the simulation experiment to check the validity of the proposed algorithm. In some simulation experiments, one mobile robot moves and observes the circumference of another mobile robot which has stopped at a certain place. This paper verified whether the mobile robot can estimate position using the measurement value when the number of observation times becomes 10 times in n/18 of observation intervals. The result of the simulation shows the effectiveness of the algorithm.

Simultaneous Position Estimation and Omnidirectional Camera Parameter Calibration for Multiple Mobile Robots

This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information gathering robotic system in unknown environment. Here, each mobile robot is not possible to know its own position. It can only estimate its own position by using the measurement value including white noise acquired by two omnidirectional cameras mounted on it. Each mobile robot is able to obtain the distance to those robots observed from the images of two omnidirectional cameras while making calibration during moving but not in advance. Simulation of three robots moving straightly shows the effectiveness of the proposed algorithm.

Precise trajectory tracking of mecanum-wheeled omnidirectional mobile robots via a novel fixed-time sliding mode control approach

This paper proposes a novel fixed-time sliding mode control approach for trajectory-tracking tasks of a mecanum-wheeled omnidirectional mobile robot.First,the idea of two-phase attractors is introduced into the domain of sliding mode control,and a new fixed-time sliding surface is proposed.Then,according to this sliding surface,a new type of nonsingular fast terminal sliding mode control algorithm is designed for the omnidirectional mobile robot,which can realize a fast fixed-time convergence property.The stability of the control system is proven scrupulously,and a guideline for control-parameter tuning is expounded.Finally,experiments are implemented to test the trajectory-tracking performance of the robot.Experimental results demonstrate the superiority of the proposed sliding surface and the corresponding control scheme in comparison with benchmark controllers.

A Stochastic Approach for Cooperative Position Estimation of Multiple Mobile Robots

This paper proposes the cooperative position estimation of a group of mobile robots, which pertbrms disaster relief tasks in a wide area. When searching the wide area, it becomes important to know a robot＇s position correctly. However, for each mobile robot, it is impossible to know its own position correctly. Therefore, each mobile robot estimates its position from the data of sensor equipped on it. Generally, the sensor data is incorrect since there is sensor noise, etc. This research considers two types of the sensor data errors from omnidirectional camera. One is the error of white noise of the image captured by omnidirectional camera and so on. Another is the error of position and posture between two omnidirectional cameras. To solve the error of latter case, we proposed a self-position estimation algorithm for multiple mobile robots using two omnidirectional cameras and an accelerometer. On the other hand, to solve the error of the former case, this paper proposed an algorithm of cooperative position estimation for multiple mobile robots. In this algorithm, each mobile robot uses two omnidirectional cameras to observe the surrounding mobile robot and get the relative position between mobile robots. Each mobile robot estimates its position with only measurement data of each other mobile robots. The algorithm is based on a Bayesian filtering. Simulations of the proposed cooperative position estimation algorithm for multiple mobile robots are performed. The results show that position estimation is possible by only using measurement value from each other robot.

Control of a 6DOF Mobile Manipulator with Object Detection and Tracking Using Stereo Vision

A supportive mobile robot for assisting the elderly is an emerging requirement mainly in countries like Japan where population ageing become relevant in near future.Falls related injuries are considered as a critical issue when taking into account the physical health of older people.A personal assistive robot with the capability of picking up and carrying objects for long/short distances can be used to overcome or lessen this problem.Here,we design and introduce a 3 D dynamic simulation of such an assistive robot to perform pick and place of objects through visual recognition.The robot consists of two major components;a robotic arm or manipulator to do the pick and place,and an omnidirectional wheeled robotic platform to support mobility.Both components are designed and operated according to their kinematics and dynamics and the controllers are integrated for the combined performance.The objective was to improve the accuracy of the robot at a considerably high speed.Designed mobile manipulator has been successfully tested and simulated with a stereo vision system to perform object recognition and tracking in a virtual environment resembling aroom of an elderly care.The tracking accuracy of the mobile manipulator at an average speed of 0.5 m/s is 90%and is well suited for the proposed application.

Fuzzy Behavior-based Control of Three Wheeled Omnidirectional Mobile Robot

In this paper, a fuzzy behavior-based approach for a three wheeled omnidirectional mobile robot(TWOMR) navigation has been proposed. The robot has to track either static or dynamic target while avoiding either static or dynamic obstacles along its path. A simple controller design is adopted, and to do so, two fuzzy behaviors "Track the Target" and "Avoid Obstacles and Wall Following" are considered based on reduced rule bases(six and five rules respectively). This strategy employs a system of five ultrasonic sensors which provide the necessary information about obstacles in the environment. Simulation platform was designed to demonstrate the effectiveness of the proposed approach.

Obstacle Avoidance Capability for Multi-Target Path Planning in Different Styles of Search

This study investigates robot path planning for multiple agents,focusing on the critical requirement that agents can pursue concurrent pathways without collisions.Each agent is assigned a task within the environment to reach a designated destination.When the map or goal changes unexpectedly,particularly in dynamic and unknown environments,it can lead to potential failures or performance degradation in various ways.Additionally,priority inheritance plays a significant role in path planning and can impact performance.This study proposes a ConflictBased Search(CBS)approach,introducing a unique hierarchical search mechanism for planning paths for multiple robots.The study aims to enhance flexibility in adapting to different environments.Three scenarios were tested,and the accuracy of the proposed algorithm was validated.In the first scenario,path planning was applied in unknown environments,both stationary and mobile,yielding excellent results in terms of time to arrival and path length,with a time of 2.3 s.In the second scenario,the algorithm was applied to complex environments containing sharp corners and unknown obstacles,resulting in a time of 2.6 s,with the algorithm also performing well in terms of path length.In the final scenario,the multi-objective algorithm was tested in a warehouse environment containing fixed,mobile,and multi-targeted obstacles,achieving a result of up to 100.4 s.Based on the results and comparisons with previous work,the proposed method was found to be highly effective,efficient,and suitable for various environments.

基于Jetson Nano的智能投送机器人系统实现

针对室内狭小空间的作业环境,提出了一种基于视觉的智能投送机器人。设计了智能投送机器人的机械结构,搭建了智能投送机器人的软硬件控制系统。利用Jetson Nano处理图像识别并搜索物体信息;以STM32F4作为机器人底盘主控芯片,采用模糊分数阶PID控制算法控制电机速度,实现了机器人精准定位、自主避障循迹、物料的分选以及投送功能。

基于双环滑模控制的全向移动工业机器人多目标点跟踪控制系统设计

全向移动工业机器人在实际应用场景中,经常处于存在较高噪音的环境中,导致多目标跟踪的性能变差,为此设计基于双环滑模控制的全向移动工业机器人多目标点跟踪控制系统;系统硬件设计了主控制器模块及主控制器芯片;在数据采集模块中配置数据采集卡,实施帧数据采集;在无线通信模块中,采用Wi-Fi无线通信技术,实现系统的远程控制、数据传输功能;系统软件部分设计基于GhostNet的改进目标检测网络,实施多目标点检测;设计基于改进SORT算法的多目标点跟踪算法,实现多目标点跟踪;设计基于双环滑模控制的多目标点跟踪控制器,实现多目标点跟踪控制;测试结果表明,静态障碍物情况下,在仓库场景下,设计系统的目标点跟踪准确性平均值为97.23%,室外场景下的目标点跟踪准确性平均值为96.37%;动态障碍物情况下,两种场景下系统的目标点跟踪准确性略低于静态障碍物情况。

基于ROS的全向轮自主移动底盘平台研制

针对机器人移动底盘在复杂环境中响应速度慢、缺乏自主移动能力的问题,研制了一种基于ROS的全向移动四轮自主导航底盘平台。该平台包含移动机器人机械底盘、激光雷达、ROS驱动的软件系统,采用STM32F407单片机系统作为软硬件转化的中间层。机械底盘设计采用“井”字构型框架,包含4个由大疆3508电机驱动的全向轮,上层ROS主机接收传感器信号并完成运动解算后通过单片机系统与底盘电机通信,并借助激光雷达和里程计实现了SLAM定位与导航,从而完成整体控制流程。系统测试结果表明,研制的ROS驱动全向轮自主移动平台响应速度快、运动平稳,在复杂环境中自主移动能力强,具有较好的精确性与鲁棒性。

全向移动机器人的神经滑模自适应PD跟踪控制

针对四轮全向机器人数学模型中未知因数的干扰,提出了一种基于神经滑模的比例微分(Proportional plus Derivative,PD)自适应跟踪控制策略。首先,对机器人的动力学模型进行分析;其次,利用反步轨迹跟踪控制器得到虚拟速度,基于虚拟输入与实际输入的误差设计PD控制器;接着,采用神经网络来逼近动力学模型中的不确定性,并利用Lyapunov定理证明了系统的稳定性。仿真和实验结果表明,该控制策略具有有效性。

基于视觉图像的全向移动机器人轨迹跟踪控制研究

机器人轨迹节点跟踪比较难,导致机器人实际轨迹偏离期望轨迹,所以设计基于视觉图像的全向移动机器人轨迹跟踪控制方法;构建全向移动机器人的运动学数学模型,以此确定机器人移动轨迹数学模型;以移动轨迹数学模型为基础,按照视觉图像划分标准对全向移动机器人运动图像的分割,通过分离目标节点的方式提取运动学特征参量,完成机器人轨迹节点跟踪处理;结合节点跟踪处理结果,将运动学不等式与误差向量作为机器人轨迹跟踪控制的约束条件,利用滑模变结构搭建轨迹跟踪控制模型,实现全向移动机器人轨迹跟踪控制;对比实验结果表明,所设计的方法应用后,全向移动机器人角速度曲线、线速度曲线与期望运动轨迹曲线之间的贴合程度均超过90%,满足全向移动机器人轨迹跟踪控制要求。

一种全方位移动机器人的运动学分析

介绍了本所开发的全方位移动机器人的机械结构 ,分析了它的运动学模型 .并在此基础上 ,讨论了几种特殊的运动方式 .最后分析了实际存在的滑动对模型的影响 .

基于EKF的全景视觉机器人SLAM算法

研究全景视觉机器人同时定位和地图创建(SLAM)问题。针对普通视觉视野狭窄,对路标的连续跟踪和定位能力差的问题,提出了一种基于改进的扩展卡尔曼滤波(EKF)算法的全景视觉机器人SLAM方法,用全景视觉得到机器人周围的环境信息,然后从这些信息中提取出环境特征,定位出路标位置,进而通过EKF算法同步更新机器人位姿和地图库。仿真实验和实体机器人实验结果验证了该算法的准确性和有效性,且全景视觉比普通视觉定位精度更高。

四轮全方位移动机器人各向相异性研究

由于全方位轮的特殊构造,使得全方位移动机器人沿不同方向运动时具有的最大速度不同,以及在不同方向上的加速性能也不同,称之为各向相异性(anisotropy).为了充分发挥全方位移动机器人的优越性,通过对4轮全方位移动机器人进行运动学、动力学建模,分析了机器人各向相异性,确定了轮系布置与最大速度曲线的相关规律,以及当机器人沿某一方向以一定加速度运动时,不同轮子上驱动电机所需提供的转矩,从而使得机器人加速运动时更好地避免轮子打滑.并且通过Matlab-ADAMS联合仿真以及实际实验,验证了分析结果的正确性.对机器人的各向相异性作了全面系统的研究,从而更清楚地表述了模型特性,为更好地控制全方位移动机器人提供了基础.

基于架空轨道的全向移动机器人运动稳定性研究

根据基于架空轨道的全向移动机器人运动特点建立了一种以控制器、驱动机构和被执行对象为开环控制的系统模型,分析被执行对象受惯性作用对系统性能的冲击干扰稳定性,通过Matlab仿真分析瞬态性能,并与无扰动系统状态进行对比。结果表明,增加速度(Kcs)反馈闭环的方法可提高系统的稳定性;改变Ka、Kc大小能使系统的动态性能保持在最优状态;采用闭环控制方法能够达到预期效果。

一种模块化全方位移动机器人的运动学分析

全方位移动机器人由三个轮式模块化单元和一个连接平台组成。轮式模块化单元是一个模块化万向单元称为MUU,具有俯仰、偏航和回转三个自由度。MUU的圆柱形铝合金外壳上安装了一系列的被动轮,这些被动轮机构使MUU成为一个大的全方位驱动轮。MUU在垂直于身体轴线方向能够提供较大驱动力,而在身体轴线方向的作用力由小被动轮卸载,从而实现万向轮的功能。高度的集成性使MUU的通讯和更换易于实现。移动机器人的运动学分析证明了该机器人的运动灵活性。最后,给出了该机器人的运动实验和仿真结果。

一种基于全向摄像机的移动机器人定位方法

研究用压缩的全向图像在移动机器人上定位和环境建模.采用Parzen窗方法估计全景图像边缘的概率密度,用FFT方法简化计算获得密度估计的实时处理效果.研究了全景图像的旋转不变特性和全景图像矢量集合的主成分提取方法,以进一步降低图像数据矢量维数.压缩数据量后,便于建立大的环境模型供移动机器人实时定位用.定位通过投影图像矢量到特征子空间和在子空间中寻找最邻近点的方法实现.提出的定位方法用于移动机器人定位系统,在室内场景多次试验获得了较理想的结果.

一种智能医疗机器人行走机构的研究

介绍了一种在移动机器人中常用的全方位移动机构—麦卡纳姆轮系的原理以及结构。然后在此基础上对其进行了运动学分析和控制系统的设计,实现了其在平面上的全方位移动。