Key words : Source term, Receding horizon path planning, Particle filter, Informative path planning
| Particl filter
Algorithm used in state estimation and probabilistic modeling is often utilized in robot engineering, autonomous vehicles, computer vision.
Example of the Particle filter : Finding the localization of a robot
| Situation
Let's assume we don't know where the robot is located in the room.
| Step
1. Start : Many tiny points(particles) are placed by the robot at various locations in the room. The points(particles) represent all possible locations where the robot can exist.
2. Movement : The robot is moving forwad with all particles surrounding it.
3. Sensor usage : It collects distance information like walls observed by surroundings.
0. Abstract
on going . .
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https://www.dbpia.co.kr/pdf/pdfAiChatView.do?nodeId=NODE09317865
This paper, published at the KSAS fall conference in 2019 was written by Prof. Park Min-gyu as the primary author and Oh Hyun-dong as the collaborative author and it is affiliated with UNIST.