The high level of English is a standard for a top student.
1. Become one of the most simple person and walk a the happiest way. The other, to fate.
2. What kind of dance do Chinese people like?
The square dancing!!! Chinese people are so keen on that. Especially middle-aged people, they are obsessed. I have participated once to keep my mother company. It was, I have to admit, kind of fun. They would usually dance to fast songs and work up a sweat. When you dance with a crowd, like the Flash Mob, you feel a sense of happiness and participation. You feel you are a part of something that is bigger than yourself. I guess that is why it is so popular.
3. “I love you, not for long, just one life time; I love you, not so deep, just till the bottom of the ocean. I love you, I do not wish for any expensive gifts, I only want your true love in return.”
4. Letting go doesn't mean that you're a quitter. It doesn't mean that you lost. It just means that you realize in that moment that's it's time to let go and move on.
5. It is our choices that show what we truly are, far more than our abilities.
6. The shortest distance between two people is a smile.
7. Time waits for no one. Treasure every moment you have.
8. There's no one that can influence the way you live your life. Sometimes, we just need a bit more confidence to stick with our choices.
9. Someday, you will find the one, who will watch every sunrise with you until the sunset of your life.
10. To live a beautiful life, one must be tolerant， without complaint or explanation.
11. After climbing a great hill, one only finds that there are many more hills to climb.
12. Do not be jealous that people have done better than you. All you need to do is to keep breaking your own record every day, for success is a fight between you and yourself.
13. people should have perseverance, otherwise will accomplish nothing.
14. A pain, is not how to forget, but in whether has the courage to start again.
15. If we define usefulness in terms of actual rewards or increased capital accumulation, and use these criteria to screen those we need to get close to, to choose what we should do, we may end up living in a world of material prosperity and inner isolation because we are unwilling to invest time in it. In the maintenance of emotion, there will be no one who can really understand own heart.
16. Normality is a paved road: It’s comfortable to walk, but no flowers grow on it.
Paper
1. Multiagent Sensor Fusion for Connected & Autonomous Vehicles to Enhance Navigation Safety
（https://www.ri.cmu.edu/wp-content/uploads/2018/01/multiagent-sensor-fusion-revised-final.pdf）
Abstract： Today, autonomous vehicle (AV) navigation systems rely solely on local sensor data feed for safe & reliable navigation. However, it is not uncommon for sensor data to contain erroneous measurements resulting in false predictions, classified as either false positives (predict non-existent obstacle) or false negatives (e.g., missed obstacle). In this paper, we propose a methodology to identify and minimize false negatives in autonomous vehicle navigation, since these are arguably the most dangerous. According to the methodology, each autonomous agent simultaneously localizes and maps its local environment. This map, in turn, is encoded into a low-resolution message and shared with nearby agents via DSRC, a wireless vehicle communication protocol. Next, the agents distributively fuse this information together to construct a world interpretation. Each agent then statistically analyzes its own interpretation with respect to the world interpretation for the common regions of interest. The proposed statistical algorithm outputs a measure of similarity between local and world interpretations and identifies false negatives (if any) for the local agent. This measure, in turn, can be used to inform the agents to update their kinematic behavior in order to account for any errors in local interpretation. The efficacy of this methodology in resolving false negatives is shown in simulation.
2. master thesis
Reliable Navigation for Autonomous Vehicles in Connected Vehicle Environments by using Multi-agent Sensor Fusion
(https://www.ri.cmu.edu/wp-content/uploads/2017/08/thesis2.pdf)
Abstract The age of intelligent vehicles is here, and with the rise in autonomous navigation we face a new challenge in finding ways to increase the safety and reliability of navigation for autonomous vehicles in dynamically changing environments. To date, most methodologies in autonomous navigation mainly rely on the data feed from local sensors. However, erroneous measurements in sensor data might reduce the overall safety and confidence in navigation. These errors may be persistent and/or temporal, and give rise to false predictions made by the autonomous agents, usually classified as either a false positive or a false negative. Though false positives may influence navigation safety in an indirect manner, false negatives directly and significantly affect it. In this thesis, we explore a methodology for sharing and fusing sensor data of closeproximity autonomous or intelligent vehicles to identify and minimize false negatives in local environment interpretation. For each agent, the methodology compares the local SLAM maps with maps generated by other close proximity agents to identify false negatives in local interpretation. As per the methodology, each autonomous agent simultaneously localizes and maps its local environment. This map, in turn, is encoded into a low-resolution message and shared over the DSRC communication protocol. Next, the agents distributively fuse this information together to build world interpretation. Each agent then statistically analyses its own interpretation with respect to the world interpretation for the common regions of interest. The proposed statistical algorithm outputs the measure of similarity between local and world interpretations and identifies false negatives (if any) for the local agent. This measure, in turn, can be used to inform the agents to change their kinematic behavior in order to account for the errors in local interpretation. Finally, each agent records the measure and instances of erroneous interpretations, which over a period of time helps analysis and quantifies the sensor health. We evaluate the qualitative and quantitative efficacy of our proposed methodology and algorithms using a widely accepted traffic simulator called SUMO in scenarios that have a high accident frequency. We use ROS in tandem with SUMO to simulate and quantify the behaviour of autonomous vehicles. Finally, we also propose a communication architecture to enforce the proposed methodology in the real world and quantify the efficacy of the communication architecture by conducting latency testing.