Terra11113/act_red_box_v5_precision_b8

ACT V5: SO-101 Precision Pick-and-Place Baseline

Task

Pick up a red cube and put it in a box.

Hardware

• SO-101 leader-follower robot arm
• External RGB camera
• NVIDIA RTX 5060 Laptop GPU

Training data

20 high-quality teleoperated demonstrations. The cube starts at a fixed reference location A.

Training configuration

• Policy: ACT
• Training steps: 20,000
• Batch size: 8
• Input: RGB image and robot joint state
• Output: SO-101 joint action chunk

Evaluation

The policy was evaluated in 10 independent autonomous real-robot trials.

Metric	Result
Successes	8 / 10
Success rate	80%

Result

This is the initial closed-loop imitation-learning baseline. The next stage adds a wrist camera, multiple cube positions, language instructions, and SmolVLA fine-tuning.

Limitations

The evaluation uses a fixed object position and a single external RGB camera. It does not yet test position, lighting, or language generalization.