Tag Archives: Robots

Dyson Released its New Vacuum Cleaner Robot: 360 Eye

This state-of-the-art vacuum cleaner robot, 360 Eye, was released by Dyson few months ago. From the official website, it can be seen that the robot uses V-SLAM technique which dramatically increases the computational overhead. To fit the computational load, I think the processor of this robot should be at least a Cortex A8 running at 1GHz or an ARM-DSP SoC, like TI DaVinci DM64xx. I think the innovative part which makes this robot unique, is the use of tank-like structure and a 360 degrees camera for video navigation:

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Figure. 360 Eye Vacuum Robot by Dyson (picture from IEEE Spectrum)

The tank structure makes this robot robust to small scale obstacles such as your carpet on the floor and small rising edges. For the idea of using a 360 degrees camera, well, I have to say it is a genius concept. A full view camera promises more contrast features and corners for the robot to navigate while it also reduce the possibility that the view of the robot is blocked by large obstacles like a human.

This is no doubt that this is the most advanced vacuum cleaner robot so far and only the newest technology of micro-processors can ensure this aggressive design. The only problem is, the cost of this robot is also considerable, thus its selling price is more than 900 dollars.

Last thing that I am wondering about is, what if this robot encounters a mirror?

( For Chinese users please visit Youku to see the video: http://v.youku.com/v_show/id_XNzc0MTMzNTA0.html )

AR.Drone Position Servoing and Visual Tracking

A demonstration of my Master’s Thesis: Visual-Based Localization and Tracking of a UGV with a Quadcopter. In this project, a visual tracking framework is designed to track the UGV with an AR.Drone quadcopter from Parrot. The system utilizes a centralized control by a ground station which is running ROS and Ubuntu 12.04 LTS.

The first two experiments were taken with the support of a global vision system which was designed using a low cost web camera. While in the last experiment, the quadcopter simply uses IMU data for navigation. The image was captured from the bottom camera of the AR.Drone and processed with OpenCV. Four PID controllers were designed to control the motion of the quadcopter to make it hold at a position or track a trajectory.

The next step is to use such a robot system for factory and infrastructure inspection. But since I have to return my quadcopter to the department, it is really problematic for me to imply this idea. Hope I can find the chance to get another AR.Drone soon.

(国内用户请访问优酷:http://v.youku.com/v_show/id_XNzczOTg0MDY0.html

机器人仿真软件V-REP

最近有幸接触到了一款非常强大的机器人动态仿真软件:V-REP。V-REP有非常完善的物理仿真引擎,支持移动机器人、飞行机器人、人型机器人、多足机器人以及多轴机械手的运动学仿真。

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V-REP的仿真程度非常高,不仅可以仿真机器人的本体与多种传感器,还支持障碍物以及地型(空中,地面,水底)的仿真。V-REP支持使用C/C++,Python,JAVA,Lua,Matlab编写脚本,十分适合于多机器人的仿真。

官方网站:

http://www.coppeliarobotics.com/

官方演示视频:

第三届谢菲尔德大学搜救机器人比赛

这个月月初参加了我们学校的搜救机器人大赛:谢菲尔德自动工程系搜救机器人比赛 (ACSE Robotic Search and Rescue Competition) 。该比赛的目标是设计一个移动机器人,通过远程视频控制的方法让其通过一个模拟的搜救环境,并在最短时间内到达终点。该场地模拟了很多搜救过程中可能出现的障碍:重型物体、斜坡、坑洼路面、吊桥、狭窄的通道等。图为当天的比赛场地:

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Figure 1.  比赛当天场地实景

这个比赛的难点在于机器人的结构必须能应对复杂的场地,并且参赛队伍在比赛过程中无法直接看见机器人所在环境,只能通过远程视频的方式对机器人进行无线控制。这次我采用的架构为Arduino兼容的大谷Wild Thumper机器人控制板 + 树莓派:由Wild Thumper控制板进行电机控制与传感器采集,并通过树莓派实现远程控制与视频传输,两个系统之间通过TTL串口进行通信。PC端使用Processing对机器人实现控制,并展示当前的运行参数与传感器数据。

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Figure 2. Wild Thumper(左) + 树莓派(右)的配置

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Figure 3. 机器人实体(正面)

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Figure 4. 机器人实体(侧面)

机器人所用的摄像头为树莓派官方最新发布的摄像头模块RaspiCam,该模块使用OV5647芯片,图像像素为300万,视频支持1080P@30fps。 摄像头模块通过软排线与树莓派的CSi接口相连接,并通过云台增加了倾斜方向的自由度。视频采集与传输使用Raspivid + Netcat + mplayer,为了提高传输速率使用了UDP协议,并且将采集像素下降到600 * 480。摄像头通过热熔胶固定在舵机云台上,图为摄像头的安装位置:

DSC01775Figure 5. 机器人摄像头特写

DSC01700 Figure 6. 无线视频传输调试

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Figure 7. 比赛现场 之1

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Figure 8. 比赛现场 之2

机器人硬件配置清单

核心主控 树莓派 Model B
辅助控制 Wild Thumper (Arduino兼容)
底盘 大谷4WD Wild Thumper Chasis
摄像头 RaspiCam + 单轴云台
传感器 3轴加速度/陀螺仪 + 3轴磁场传感器
电源供电 20C/5000mAh 2s锂聚合物电池+ USB备份电源5V 6000mAh

机器人电机驱动器YFWind

YFWind是专门用于中小型移动机器人的电机驱动模块,该模块支持双路有刷电机驱动,可提供5A持续电流,6A瞬间电流,电路留有YFSMega专用接口,也可使用其它控制器驱动。模块留有电源指示灯、正反转工作指示灯,并具有反接、过热关断、输出短路等保护。

模块的主要特性如下所示:

控制对象

5 – 12V 直流电机

负载电流

5A持续,6A峰值

通道数量

两路

控制方式

GPIO

调速方式

PWM

指示LED

电源、正转、反转

保    护

反接保护、过热关断保护、输出短路保护

接  口

单排插针*2,或10口输出(与YFSMega兼容)