deer7777777's Stars
zhm-real/PathPlanning
Common used path planning algorithms with animations.
lehaifeng/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
bojone/attention
some attention implements
ZYunfeii/UAV_Obstacle_Avoiding_DRL
This is a project about deep reinforcement learning autonomous obstacle avoidance algorithm for UAV.
semitable/robotic-warehouse
Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment
JinleiZhangBJTU/ResNet-LSTM-GCN
Code for Deep-learning Architecture for Short-term Passenger Flow Forecasting in Urban Rail Transit
LazyFalcon/D_star_PathPlanning
Simple Matlab implementation of D*Lite, Focussed D*, A*, for dynamic path planning for mobile robots
ZYunfeii/DRL_algorithm_library
This is a reinforcement learning algorithm library. The code takes into account both performance and simplicity, with little dependence.
tud-amr/mrca-mav
Collision avoidance for mavs in dynamic environments using model predictive control
GasserElAzab/6-DOF-DLR-robot-simulation-in-Matlab-Simulink
This is the full analysis of the forward, inverse kinematics, trajectory planning, path planning, and controlling the end effector.
HCPLab-SYSU/PVCGN
code for "Physical-Virtual Collaboration Graph Network for Station-Level Metro Ridership Prediction"
PingH129/A-deep-learning-approach-for-multi-attribute-data_-A-study-of-train-delay-prediction-in-railway-syst
Code for paper: A deep learning approach for multi-attribute data_ A study of train delay prediction in railway systems
JinleiZhangBJTU/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
JinleiZhangBJTU/ASTGCN
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019
muAluo-Juan/high-speed-railway-network
code for the generation of a high-speed railway network dataset
JinleiZhangBJTU/DeepST
Deep Learning for Spatio-Temporal Data
JinleiZhangBJTU/PVCGN
code for "Physical-Virtual Collaboration Graph Network for Station-Level Metro Ridership Prediction"