@@Vamanation Perhaps, but that's only useful if every road has retroreflective paint strips. Waymo does a lot of its most impressive stuff with its cameras and AI. Tesla FSD beta understands it surroundings very well with cameras and radar, even if it's not 100% there on doing the right thing in every situation.
Is not it easier using radar instead LiDAR (or at least do sensor fusion) in order to get an advantage in extreme weather conditions or/else in the night mode?
Hello, I wonder that multi-object tracking result comes from the UKF filter & Hungarian AL. Also, I would like to know your know-how, a paper or technical document that I can refer to for your great tracking technology.
tracking is hangarians and pseudo-EKF. I use a simpler method than JPDA or MHT. I believe that know-how is very important when it comes to tracking. Tracking is currently being rewritten to be proper.
@@yukihirosaito7783 Thank you very much for your answer. I expect a new tracking algorithm. I have two questions. I wonder if 2D tracker is also developed in the current version, and cost of tracking algorithm of the current version.
Soon all code will be open source. Prediction is based on following papers. 1. Optimal trajectory generation for dynamic street scenario in a frenet frame 2. Vehicle trajectory prediction based on motion model and maneuver recognition
detection is deep learning based point cloud instance segmentation. tracking is hangarians and pseudo-EKF. I use a simpler method than JPDA or MHT. I believe that know-how is very important when it comes to tracking. code is here : github.com/tier4/AutowareArchitectureProposal github.com/tier4/Pilot.Auto/tree/master/perception/object_recognition Tracking is currently being rewritten to be proper.
highly depth information using LiDAR. Well done
Using transformers model in domain adaptation for lidar sensor
any suggestion for this approach ?
If this is just lidar, how does it see crosswalks. I assume those are from HD maps. There is no autonomous driving without solving the vision problem.
Ofcourse its from some streetUI here but LiDAR can be used in case of retroreflective paint strips.
@@Vamanation Perhaps, but that's only useful if every road has retroreflective paint strips. Waymo does a lot of its most impressive stuff with its cameras and AI. Tesla FSD beta understands it surroundings very well with cameras and radar, even if it's not 100% there on doing the right thing in every situation.
could you provide the code for object tracking for lidar data
Is not it easier using radar instead LiDAR (or at least do sensor fusion) in order to get an advantage in extreme weather conditions or/else in the night mode?
Hello, I wonder that multi-object tracking result comes from the UKF filter & Hungarian AL. Also, I would like to know your know-how, a paper or technical document that I can refer to for your great tracking technology.
tracking is hangarians and pseudo-EKF. I use a simpler method than JPDA or MHT. I believe that know-how is very important when it comes to tracking.
Tracking is currently being rewritten to be proper.
@@yukihirosaito7783
Thank you very much for your answer. I expect a new tracking algorithm.
I have two questions. I wonder if 2D tracker is also developed in the current version, and cost of tracking algorithm of the current version.
Is it work for quanergy M8 lidar?
looks impressive, and I’ve to Predict the Pedestrian using only Lidar data. It would be really helpful if you could provide me with any suggestions ?
leg_track
Are you using the autoware framework?
yes
github.com/tier4/AutowareArchitectureProposal
Hi, I was wondering does the prediction result come from the kalman filter? Or there is an separate algorithm for prediction
Soon all code will be open source.
Prediction is based on following papers.
1. Optimal trajectory generation for dynamic street scenario in a frenet frame
2. Vehicle trajectory prediction based on motion model and maneuver recognition
@@yukihirosaito7783 ]with is your github name?
Hello, did you using point pillars deep learning model?
this is not point coud instance segmentation, not point pillars.
However, I have recently found a better method and am in the process of changing it.
can you provide the code? thanks
useing kalman?
Whats the cost ?
Using gtx 1080, detection is 20msec, tracking is a few milliseconds.
what used algorithm?
detection is deep learning based point cloud instance segmentation.
tracking is hangarians and pseudo-EKF. I use a simpler method than JPDA or MHT. I believe that know-how is very important when it comes to tracking.
code is here : github.com/tier4/AutowareArchitectureProposal
github.com/tier4/Pilot.Auto/tree/master/perception/object_recognition
Tracking is currently being rewritten to be proper.