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from lerobot.common.datasets.utils import build_dataset_frame, hw_to_dataset_features
from lerobot.common.policies.act.modeling_act import ACTPolicy
from lerobot.common.robots.lekiwi import LeKiwiClient, LeKiwiClientConfig
from lerobot.common.utils.control_utils import predict_action
from lerobot.common.utils.utils import get_safe_torch_device
NB_CYCLES_CLIENT_CONNECTION = 1000
robot_config = LeKiwiClientConfig(remote_ip="172.18.134.136", id="lekiwi")
robot = LeKiwiClient(robot_config)
robot.connect()
policy = ACTPolicy.from_pretrained("pepijn223/act_lekiwi_circle")
policy.reset()
obs_features = hw_to_dataset_features(robot.observation_features, "observation")
print("Running inference")
i = 0
while i < NB_CYCLES_CLIENT_CONNECTION:
obs = robot.get_observation()
observation_frame = build_dataset_frame(obs_features, obs, prefix="observation")
action_values = predict_action(
observation_frame, policy, get_safe_torch_device(policy.config.device), policy.config.use_amp
)
action = {key: action_values[i].item() for i, key in enumerate(robot.action_features)}
robot.send_action(action)
i += 1
robot.disconnect()
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