Artit Visatemongkolchai

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This paper describes the use of two sequential machine learning techniques for building a mobile robot's motion model, which is an essential component in SLAM algorithms. First, the recursive least squares (RLS) algorithm is used to build a static motion model. RLS can learn motion model parameters as soon as new data (the robot's poses from odometry(More)
For moving target search algorithms, we are considering the case of heuristic search where the goal may change during the course of the search. One motivating application lies with navigation of an autonomous police vehicle chasing a villain [5] in a possibly initially unknown environment under real-time constraints. In this scenario, we would like to(More)
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