Råvarornas supercykel har börjat och ädelmetallerna når nya ATH varje dag. Dessutom, uppdatering på tyska case och den svenske konsumenten.
https://t.co/kExILdF2CM
Retweeta gärna!
Råvarornas supercykel har börjat och ädelmetallerna når nya ATH varje dag. Dessutom, uppdatering på tyska case och den svenske konsumenten.
https://t.co/kExILdF2CM
Retweeta gärna!
🌟 Breaking News!🌟I’m beyond excited to announce that my research on radar odometry estimation, published in IEEE Transactions on Robotics (T-RO), has been awarded the Best Paper Award in Computer & Robot Vision! 🎉🤖
https://t.co/PNw5yK8qnA
Thrilled to announce the IEEE RAS Computer & Robot Vision Best Paper Award for 'Lidar-Level Localization With Radar?'.
Congrats to authors @DanielPlinge, @mcg_magnusson, Anas Alhashimi, @AchimJLil, and Henrik Andreasson!
Learn more here: https://t.co/ndNaLZXqkJ
@RpsAgainstTrump Wrong, and super easy to verify.
Military contributions between Europe and US is similar according to https://t.co/t4vmjVA9lq.
For total support, including financial and humanitarian, EU with its countries has contributed more.
CFEAR_Radarodometry_code_public
Efficient and accurate spinning radar odometry in C++ / ROS.
https://t.co/CjeDjCgXkG
"Lidar-level localization with radar? The CFEAR approach to accurate, fast and robust large-scale radar odometry in diverse environments"
Our work on Radar SLAM has been published in RA-L for presentation in #IROS2023. The article presents a method for highly robust loop closure - enabling reliable creation of highly accurate maps, using only a 2D Navtech Radar. Code will be released here:
https://t.co/vAHsA3Yzg1
Is fast and robust #radar#odometry, with close to 1% drift possible? Yes!🤖
The journal version of CFEAR is now published in T-RO (https://t.co/pOlAaBxd87).
Try our code (https://t.co/fApX7jZdFN) #lidar#robotics