BiGym 2.0: Benchmarking Learned and Agent-Developed Policies for Humanoid Household Manipulation
Humanoid household manipulation requires the arms to act while the body balances, steps and changes posture. We present BiGym 2.0, an adaptation of BiGym for the Unitree G1 across 20 household tasks using a unified whole-body controller for demonstration and evaluation. The suite provides 60 native human virtual-reality demonstrations per task with synchronised multi-camera views and full-body execution records. We benchmark vision-language-action fine-tuning, imitation learning, demo-driven reinforcement learning, and cold-start coding agents given the interaction budget of online reinforcement learning. With the same onboard views, proprioception and whole-body controller for every meth...
| Authors | Zexi Zhang, Zecheng Zhu, Zidong Chen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 6 October 2026 |
| Last updated at source | 8 October 2026 |
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- SWIRL-Lab/bigym-g1-native60Dataset · cited by
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