# GNNHIM **Repository Path**: bupt_htl/gnnhim ## Basic Information - **Project Name**: GNNHIM - **Description**: Dynamic Motion Planning Model for Multi-Robot using Graph Neural Network and Historical Information - **Primary Language**: Python - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2022-11-28 - **Last Updated**: 2023-11-10 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Dynamic Motion Planning Model for Multi-Robot using Graph Neural Network and Historical Information ## Requirements ``` seaborn>=0.11.1 easydict>=1.9 matplotlib>=3.3.3 numpy>=1.19.4 scipy>=1.4.1 tensorboardX>=2.1 torch==1.7.1 torchvision==0.8.2 scikit-image>=0.14.0 scikit-learn>=0.19.1 hashids==1.3.1 torchsummaryX==1.3.0 ``` ## How to Run #### Generate different scenarios Note: make sure libyaml installed correctly. ``` python generateScenarios/GenerateMap.py --random_map --gen_CasePool --gen_map_type random --chosen_solver ECBS --map_width 100 --map_density 0.1 --map_complexity 0.002 --num_dataset 5 --path_save /jinpeng/GNN/SCIMap python generateScenarios/CasesSolver.py --loadmap_TYPE random --random_map --gen_CasePool --chosen_solver ECBS --map_width 20 --map_density 0.1 --map_complexity 0.005 --num_agents 10 --num_dataset 250 --num_caseSetup_pEnv 50 --path_save /jinpeng/GNN/SCIMap/solution --path_loadSourceMap /jinpeng/GNN/SCIMap/map100x100_density_p1 python generateScenarios/DataGenerateYaml.py --num_agents 10 --map_w 20 --map_density 0.1 --div_train 3 --div_valid 1 --div_test 2 --div_train_IDMap 0 --div_test_IDMap 1 --div_valid_IDMap 2 --solCases_dir /jinpeng/GNN/SCIMap/solution/ --dir_SaveData /jinpeng/GNN/SCIMap/ --guidance Project_G ``` #### Initial training ``` python main.py configs/Configs.json --mode train --best_epoch --map_w 20 --nGraphFilterTaps 3 --num_agents 10 --trained_num_agents 10 --batch_numAgent ``` #### Test ``` python configs/Configs.json --mode test --best_epoch --log_time_trained 1662453875 --nGraphFilterTaps 3 --trained_num_agents 10 --trained_map_w 20 --commR 7 --map_w 20 --num_agents 10 --num_testset 4500 --GSO_mode dist_GSO --action_select exp_multinorm --guidance Project_G --CNN_mode Default --batch_numAgent --tb_ExpName GNN_Resnet_3Block_distGSO_baseline_128 ```