Source note
OpenEAI-Platform: An Open-source Embodied Artificial Intelligence Hardware-Software Unified Platform
Vision Language ActionRobot Foundation ModelOpen Robot HardwareRobot Data ScalingReal World Manipulation
Summary
OpenEAI-Platform pairs a $790 open 6+1 DoF arm with OpenEAI-VLA, a Qwen3-VL-4B robot policy trained with public robot and multimodal data. It targets reproducible real-world manipulation, where closed hardware, private training data, and mismatched dataset formats limit comparison and data collection.
Problem
- Real-world VLA work often depends on private datasets and incomplete training code, so other groups cannot reproduce or extend results.
- Commercial 6+1 DoF arms cost about $1.5k-$40k+ and expose limited low-level control, which blocks cheap data collection and controller research.
- Open robot datasets use different state/action conventions, which makes cross-dataset pretraining and transfer harder.
Approach
- OpenEAI-Arm is a 6+1 DoF desktop manipulator; its link geometry is chosen by NSGA-III over MDH parameters using manipulation operability and endurance efficiency objectives.
- The controller combines dynamics feedforward PID, friction compensation, rolling action-chunk interpolation, and jerk-bounded S-curve timing to turn VLA action chunks into smooth joint commands.
- OpenEAI-VLA uses Qwen3-VL-Instruct 4B with learnable query tokens that compress image, text, and instruction features into fixed-length conditioning.
- An 18-layer Diffusion Transformer action head with 32 attention heads predicts continuous action chunks through conditional flow matching.
- Training has two stages: pretrain on converted Open X-Embodiment subsets, then fine-tune on small OpenEAI-Arm demonstrations mixed with COCO, VQA-v2, and PixMo-Points.
Results
- OpenEAI-Arm material cost is $0.79k, compared with $8.60k for ARX R5 and $2.16k for AgileX Piper in the table.
- The arm weighs 3.3 kg, compared with 3.9 kg for ARX R5 and 4.2 kg for Piper.
- Manipulation operability is 0.547, nearly matching ARX R5 at 0.546 and above Piper at 0.179.
- Endurance efficiency is 0.567, above ARX R5 at 0.529 and below Piper at 0.846.
- The evaluation covers 4 real-world tasks: Clean Table, Make Tea, Fold Towel, and Fold T-shirt.
- The excerpt claims OpenEAI-VLA has success rates comparable to π0 while using limited public pretraining data, but the provided text does not include the success-rate numbers.