![]() ![]() ▲ Demo of the RPLiDAR-A1 and Hector Mapping (YouTube) ▲ Demo of the LCS filter on an autonomous driving dataset Our experts are dependent on trust factors’ covariance under the geometric definitions to ignore, emerge and compare detected landmarks. The interactive learning feed between each expert increases the consistency of detected landmarks that works against overwhelming detected features in crowded scenes. The proposed filter applies detection, tracking and learning to each defined expert to extract higher level information for judging scenes without over-calculation. The Line–Circle–Square (LCS) filter, claims that mobile robots without a large database for object recognition and highly advanced prediction methods can deal with incoming objects that the camera captures in real-time. ![]() Robotics and Autonomous Systems (2020): 103732. ![]() “Line-Circle-Square (LCS): A multilayered geometric filter for edge-based detection”. Seyed Amir Tafrishi, Xiaotian Dai, and Vahid Esmaeilzadeh Kandjani. Below is a selection of my robotics projects that were built for research (or just as a hobbist). Robotics is not only part of my research but also where my passion is - I am a robot enthusiast and I have started building robots since 2009 (when I was a 2nd year undergraduate student). ![]()
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