Robotics
ONNX
LeRobot
rsl_rl
isaaclab
isaac-sim
strands-robots
reinforcement-learning
franka
reach
ppo
agents
sim2sim
Eval Results (legacy)
Instructions to use cagataydev/strands-isaaclab-reach-franka-policy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use cagataydev/strands-isaaclab-reach-franka-policy with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 2,772 Bytes
7e98ac0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 | {
"task": "Isaac-Reach-Franka",
"checkpoint": "runs/c3_agent_sweep/1e-3_s1/logs/rsl_rl/reach_franka/2026-09-29_05-04-21_isaaclab-20260929-050417-05a8c9c0dbae/model_299.pt",
"episodes_requested": 12,
"frames": 360,
"overrides": [],
"cam": "fixed",
"cam_name": "front",
"res": [
320,
240
],
"play_mode": true,
"seed": 7,
"cmd": "/home/ubuntu/strands-robots-isaac-test/isaaclab-research/.venv/bin/python examples/record_trained_policy.py --task Isaac-Reach-Franka --checkpoint runs/c3_agent_sweep/1e-3_s1/logs/rsl_rl/reach_franka/2026-09-29_05-04-21_isaaclab-20260929-050417-05a8c9c0dbae/model_299.pt --episodes 12 --frames 360 --cam fixed --cam_name front --eye 1.6,0.9,0.9 --target 0.4,0,0.3 --task_str reach the commanded end-effector pose --robot_type franka_panda --root rec/reach-franka/ds --repo_id cagataydev/strands-isaaclab-reach-franka",
"actor_obs_groups": [
"policy"
],
"joint_names": [
"panda_joint1",
"panda_joint2",
"panda_joint3",
"panda_joint4",
"panda_joint5",
"panda_joint6",
"panda_joint7",
"panda_finger_joint1",
"panda_finger_joint2"
],
"action_names": [
"arm_action.panda_joint1",
"arm_action.panda_joint2",
"arm_action.panda_joint3",
"arm_action.panda_joint4",
"arm_action.panda_joint5",
"arm_action.panda_joint6",
"arm_action.panda_joint7"
],
"action_dim": 7,
"fps": 30,
"step_dt": 0.03333333333333333,
"env_build_s": 15.9,
"policy_obs_dim": 32,
"jit_vs_rslrl_max_abs": 2.980232238769531e-07,
"debug": [
{
"f": 0,
"cam_pos_w0": [
5.349999904632568,
-1.600000023841858,
0.8999999761581421
],
"root_pos_w0": [
3.75,
-2.5,
0.0
]
},
{
"f": 1,
"cam_pos_w0": [
5.349999904632568,
-1.600000023841858,
0.8999999761581421
],
"root_pos_w0": [
3.75,
-2.5,
0.0
]
},
{
"f": 10,
"cam_pos_w0": [
5.349999904632568,
-1.600000023841858,
0.8999999761581421
],
"root_pos_w0": [
3.75,
-2.5,
0.0
]
}
],
"policy_ms_per_step_all_envs": 4.1,
"env_ms_per_step": 146.98,
"playback_envs": [
6,
4,
0,
5
],
"cam_mean": 207.83623842592593,
"record_s": 6.8,
"episodes_saved": 12,
"kept_envs": [
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11
],
"episode_len": [
249,
55,
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22,
253,
132,
360,
14,
9,
9,
88,
17
],
"episode_return": [
-0.829,
0.05,
0.213,
0.264,
-0.967,
-0.229,
-2.107,
0.279,
0.297,
0.303,
-0.06,
0.252
],
"episode_end": [
"terminated",
"terminated",
"terminated",
"terminated",
"terminated",
"terminated",
"time_out",
"terminated",
"terminated",
"terminated",
"terminated",
"terminated"
],
"mean_return": -0.211,
"total_frames": 1230,
"total_wall_s": 91.1
} |