QRP123/mult-skill-act-models

Mult-skill ACT Models

Multi-skill Action Chunking Transformer models for Piper dual-arm robot.

Models

Model	Description
point_classifier/	ResNet-18 point classifier (10 classes: point1-point10)
exp1_all_points/	ACT policy trained on all 150 episodes (10 points combined)
exp2_point1/ ~ exp2_point10/	ACT policies trained per-point (15 episodes each)
exp3_act_x/	Experimental ACT policy

Normalization

normalization/ contains pre-computed normalization constants for each dataset:

• all_points_v30_norm.py - Stats from combined dataset
• point1_v30_norm.py ~ point10_v30_norm.py - Stats from per-point datasets

Usage

Download all models

pip install huggingface_hub
huggingface-cli download QRP123/mult-skill-act-models --repo-type model --local-dir ./models

Point Classifier Inference

from point_classifier_model import PointClassifier
import torch

checkpoint = torch.load("point_classifier/point_classifier_best.pth")
model = PointClassifier(num_classes=10, pretrained=False)
model.load_state_dict(checkpoint["model_state_dict"])

Robot Setup

• Robot: Piper dual-arm (7D + 7D = 14D state/action)
• Cameras: fisheye_left, fisheye_right, wide_mid, wide_top (256x256)
• FPS: 30