Pinned Repositories
_data_handle_mmp
Contains "Dataset" and "DataHandler" for motion prediction tasks
DataGenerator-StanfordDroneDataset
This is used to generate datasets from raw videos of the Stanford Drone Dataset (SDD).
Dynamic-Obstacle-Avoidance-SWTA-MPC
This repository contains the code to execute the simulated system for predictive dynamic obstacle avoidance based on multimodal motion prediction and model predictive control.
DyObAv-MPCnEBM-Warehouse
DyObAv-MPCnEBM-Warehouse-ROS2
DyObAv-MPCnWTA-Warehouse
Dynamic obstacle avoidance for mobile robots by combining deep learning motion prediction and MPC trajectory generation.
M3P-MDN-CASE2021
The evaluation code for the related paper published on IEEE CASE2021.
M3P-MDN-Pytorch
Use MDNs to do multimodal motion prediction on synthetic dataset.
TrajGenAvo-NMPC-OpEn
Use NMPC and reference generated by A-star to plan trajectories.
TrajTrack-MPCnDQN-RLBoost
Use DQN to boost MPC computation for dynamic obstacle avoidance.
Woodenonez's Repositories
Woodenonez/DyObAv-MPCnWTA-Warehouse
Dynamic obstacle avoidance for mobile robots by combining deep learning motion prediction and MPC trajectory generation.
Woodenonez/TrajTrack-MPCnDQN-RLBoost
Use DQN to boost MPC computation for dynamic obstacle avoidance.
Woodenonez/TrajGenAvo-NMPC-OpEn
Use NMPC and reference generated by A-star to plan trajectories.
Woodenonez/DataGenerator-StanfordDroneDataset
This is used to generate datasets from raw videos of the Stanford Drone Dataset (SDD).
Woodenonez/Dynamic-Obstacle-Avoidance-SWTA-MPC
This repository contains the code to execute the simulated system for predictive dynamic obstacle avoidance based on multimodal motion prediction and model predictive control.
Woodenonez/M3P-MDN-CASE2021
The evaluation code for the related paper published on IEEE CASE2021.
Woodenonez/_data_handle_mmp
Contains "Dataset" and "DataHandler" for motion prediction tasks
Woodenonez/DyObAv-MPCnEBM-Warehouse
Woodenonez/DyObAv-MPCnEBM-Warehouse-ROS2
Woodenonez/M3P-MDN-Pytorch
Use MDNs to do multimodal motion prediction on synthetic dataset.
Woodenonez/M3P-SWTA-Pytorch
Use WTA loss with Clustering and Gaussian Fitting (WTA+CGF) to do multimodal motion prediction.
Woodenonez/MotionSimulationCollection
Woodenonez/pylaser2d
A small laser scanner / lidar simulator in Python.
Woodenonez/TrajGenAvo-NMPC-OpEn-v2
Woodenonez/woodenonez
Woodenonez/woodenonez.github.io
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