Skip to content

[Question]: issac sim无法正确加载或切换场景 #275

@LeslieLaw0925

Description

@LeslieLaw0925

Question

作者你好,我在运行issac sim环境的evaluation,想要查看可视化的评估过程,在配置文件作了如下设置:

env=EnvCfg(
        env_type='internutopia',
        env_settings={
            'use_fabric': True,  # Please set use_fabric=False due to the render delay;
            'headless': False,
        },
    ),

issac sim启动之后,发现一直卡在下面这个画面,随着episode的切换,也没有任何反应,依旧是卡着。

Image

但是,logs下面的video目录记录的画面和视频是正常的,能够输出正确的运动过程和画面。

配置如下:
internnav版本:0.3.0
issac sim版本:4.5.0
internutopia版本:2.2.1
config如下:

# from scripts.eval.configs.agent import *
from internnav.configs.agent import AgentCfg
from internnav.configs.evaluator import (
    EnvCfg,
    EvalCfg,
    EvalDatasetCfg,
    SceneCfg,
    TaskCfg,
)

eval_cfg = EvalCfg(
    agent=AgentCfg(
        server_port=8023,
        model_name='internvla_n1',
        ckpt_path='',
        model_settings={
            'env_num': 1,
            'sim_num': 1,
            'model_path': "checkpoints/InternVLA-N1-DualVLN",
            'camera_intrinsic': [[585.0, 0.0, 320.0], [0.0, 585.0, 240.0], [0.0, 0.0, 1.0]],
            'width': 640,
            'height': 480,
            'hfov': 79,
            'resize_w': 384,
            'resize_h': 384,
            'max_new_tokens': 1024,
            'num_frames': 32,
            'num_history': 8,
            'num_future_steps': 4,
            'device': 'cuda:0',
            'predict_step_nums': 32,
            'continuous_traj': True,
            'infer_mode': 'partial_async',  # You can choose "sync" or "partial_async", but for this model, "partial_async" is better.
            # debug
            'vis_debug': True,  # If vis_debug=True, you can get visualization results
            'vis_debug_path': './logs/test_n1/vis_debug',
        },
    ),
    env=EnvCfg(
        env_type='internutopia',
        env_settings={
            'use_fabric': True,  # Please set use_fabric=False due to the render delay;
            'headless': False,
        },
    ),
    task=TaskCfg(
        task_name='test_n1',
        task_settings={
            'env_num': 1,
            'use_distributed': False,  # If the others setting in task_settings, please set use_distributed = False.
            'proc_num': 1,
            'max_step': 1000,  # If use flash mode,default 1000; descrete mode, set 50000
        },
        scene=SceneCfg(
            scene_type='mp3d',
            scene_data_dir='data/scene_data/mp3d_pe',
        ),
        robot_name='h1',
        robot_flash=True,  # If robot_flash is True, the mode is flash (set world_pose directly); else you choose physical mode.
        flash_collision=False,  # If flash_collision is True, the robot will stop when collision detected.
        robot_usd_path='data/Embodiments/vln-pe/h1/h1_internvla.usd',
        camera_resolution=[640, 480],  # (W,H)
        camera_prim_path='torso_link/h1_1_25_down_30',
        one_step_stand_still=True,  # For dual-system, please keep this param True.
    ),
    dataset=EvalDatasetCfg(
        dataset_type="mp3d",
        dataset_settings={
            'base_data_dir': 'data/vln_pe/raw_data/r2r',
            'split_data_types': ['val_unseen'],  # 'val_seen'
            'filter_stairs': True,  # For iros challenge, this is False; For results in the paper, this is True.
            # 'selected_scans': ['zsNo4HB9uLZ'],
            # 'selected_scans': ['8194nk5LbLH', 'pLe4wQe7qrG'],
        },
    ),
    eval_type='vln_distributed',
    eval_settings={
        'save_to_json': True,
        'vis_output': True,
        'use_agent_server': True,  # If use_agent_server=True, please start the agent server first.
    },
)

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions