English:listening、speaking、reading、writing、translation
1. What’s your favourite part of your home?
I don’t think I have too many choices to choose from. After all, I only have one part all to myself---that is, my bedroom. I have, in my bedroom, a state-of-the-art gaming device----the latest X-box. It’s a kick-ass device. You can literally do anything with it. Virtual running, batting, shooting, white-water rafting and horse-back riding, you name it. When I am in my bedroom, I can play however I want without disturbing anyone. I think it is the place I would go to forget all my problems and recharge my battery.
2. Sorrow is hushed into my heart, like the evening among the silent trees.
3. You‘d better not miss two things, the last bus to home and the person who deeply love you.
4. Always find time for the things that make you feel happy to be alive.
5. In many times in life, no matter when you start, it is important to start after, don‘t give up.
MATLAB && ROS
1. How Do Autonomous Systems “See”? （https://blogs.mathworks.com/racing-lounge/2018/09/12/autonomous-systems-sensors/）
There are many challenges around the world that focus on learning autonomous perception and navigation using low-cost ground vehicle platforms. Here are a few that we support, which consist of similar tasks:
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- TurtleBot3 AutoRace
- Droid Racing Challenge
- Rose-Hulman High School Autonomous Vehicle Challenge
Our previous blog post covered the Rose-Hulman High School Autonomous Vehicle Challenge. In this post, we will dive deeper into the TurtleBot3 AutoRace. This student competition contains a ready-to-go simulation package and a set of tutorials.
TurtleBot3 is also designed to be an educational low-cost platform for the Robot Operating System (ROS). ROS is a software framework that, among many things, lets users easily switch between simulation and hardware. As we have discussed in a previous blog post, MATLAB and Simulink has an interface to ROS. This made it possible for us to collect data from the AutoRace simulation and put together some quick examples.
ROS is also known for containing specialized message types that represent common sensors used in autonomous systems. At the same time, MATLAB and Simulink have toolboxes for computer vision, motion planning, and automated driving. So, in the rest of this post I will bridge these two tools by exploring common sensor types a few examples:
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- Vision sensors: Various types of cameras (mono vs. stereo, color vs. infrared, etc.)
- Line-of-sight sensors: Ultrasonic sensors, radar, and lidar.
2. Introducing Autonomous Systems to High School Students
（https://blogs.mathworks.com/racing-lounge/2018/08/29/autonomous-systems-high-school-students/）
3. Rose-Hulman High School Autonomous Vehicle Challenge
（https://www.mathworks.com/academia/student-competitions/high-school-autonomous-vehicle-challenge.html）
4. matlab guide to operate turtlebot 3
（https://www.mathworks.com/matlabcentral/answers/417237-matlab-guide-to-operate-turtlebot-3#answer_336396?s_tid=prof_contriblnk）
5. A "Getting Started" Guide for Developers Interested in Robotics (http://learn.turtlebot.com/)
6. We Want You to Learn TurtleBot (and Robotics)! (http://learn.turtlebot.com/2015/02/01/1/)
The goal of this article series is to get web, mobile, and maker developers programming with ROS via the TurtleBot development platform. We hope you will see the amazing possibilities and opportunities, dive in and never look back.
7. We Want You to Learn TurtleBot in Simulation! （http://learn.turtlebot.com/2015/02/03/1/）
A robotics simulator is used to create embedded applications for a robot without depending physically on the actual machine. The good part is that most applications used in simulation can be transferred to physical robots without major changes.
Unfortunately, despite all advantages, even the best software cannot simulate the real world perfectly.
paper
1. Design of a multi-purpose low-cost mobile robot for research and education
(https://www.researchgate.net/publication/281208652_Design_of_a_Multi-purpose_Low-Cost_Mobile_Robot_for_Research_and_Education) (just so so !!!)
Abstract. Mobile robots are commonly used for research and education. Although there are several commercial mobile robots available for these tasks, these robots are costly and do not always meet the characteristics needed for certain applications, being very difficult to adapt because they have proprietary software and hardware. In this paper, we present the design ideas, development and applications of a mobile robot called ExaBot. Our main goal was to obtain a single multi-purpose lowcost robot -more than ten times cheaper than commercially available platforms- that can be used not only for research, but also for outreach and education activities. Its body, sensors, actuators, processing units and control board are well detailed. The software and printed circuit board developed for this project are open source to allow the robotics community to use and upgrade the current version. Finally, different configurations of the ExaBot are presented, showing several applications that fulfill the requirements this robotic platform was designed for.
Conclusions and Future Work In this paper, we present the design ideas, development and applications of the new mobile robot ExaBot. Our main goal was to obtain a multi-purpose low-cost robot- i.e., ten times cheaper than commercially available research robots- that could be used not only for research, but also for outreach and education. The main requirement to achieve a low cost robot that can be used for such diverse fields is that the robot is highly reconfigurable. Hence, the ExaBot was designed with many sensors that can be optionally installed, and built-in sensor expansion ports. The high level processing unit and the communication protocol are also reconfigurable. In this manner, many different configurations of the ExaBot have been built and used; keeping the base cost of the robot at around $250. We have successfully used them for research activities, mainly in vision-based autonomous navigation; for undergraduate education; and for robotic-centered courses at K-12 education and other outreach activities. As future works, we are planning to build the mechanical chassis ourselves to further lower costs. Moreover, further research experiments are planned using the recently incorporated sensors (laser scan and gyro-compensated digital compass), as well as new processing elements such as a BeagleBoard.
broaden your horizon
1. http://www.aisl.cs.tut.ac.jp/research.html
2. http://www.cs.tut.ac.jp/lab/e-mr.html