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Unsafe actions halt real-robot trials of GPT-6 Astra as a robot policy

Wenbo Zhang and colleagues ran GPT-6 Astra as a zero-shot robot manipulation policy on the 42 simulated RoboDojo tasks. It ranked above all 40 public policies on that board. On real arms, the team halted testing after the model repeatedly issued unsafe actions. The paper says some incidents damaged hardware and nobody was hurt.

Open original source arxiv.org · Wenbo Zhang et al.

Claimed
Why this evidence label?

Paper text (section 5 and conclusion) describes the halted real-robot protocol and hardware damage; no video or logs of the incidents.

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The source's own preview image, from arxiv.org.

Briefing

In simulation Astra reached a 22.48% average success rate over 2,100 trials with no robot finetuning. GPT-5.5 and DeepSeek-Flash, run through the same interface, scored 0.88% and 1.92%. Astra did well on tasks that need semantic understanding and poorly on precision, dynamic control and two-arm coordination.

The official RoboDojo-Real protocol was never completed. The paper keeps 33 trials on ARX X5, Piper and Piper X arms as diagnostic material, and 1 of them was a full success. The authors write that Astra interpreted tasks more reliably than it executed them safely, and they call for independent safety checks and stop mechanisms instead of trust in the model's judgment.

The incidents are described in text; the paper has no video or logs of them.

“Unsafe actions halted our real-robot trials.”

Wenbo Zhang et al., in the source on arxiv.org

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