Here we provide a demo for the robot base registration, where the related-config* file is also given in registration.
a. Replace pretrain in indoor.yaml with the path of your model. You can download our trained model from here. For example,
pretrain: './model_best_loss.pth'b. You can train your own model using (if you have a robot base other than UR3e, UR5 and UR5e)
python main.py configs/train/indoor.yaml
c. Open PredatorRegistration-demo.ipynb to test. The function for PREDATOR is
tsfm, consuming_time = PredatorRegistration(src_data, tgt_data)