Event
BioAgent autonomously acquires long-horizon laboratory protocol skills
1 reports · 1 sources
Gaojing Zhang and other authors published a paper proposing an embodied agent, BioAgent, for long-horizon laboratory protocols: it matches human-reviewed requirements with verified skills, selects tool implementations for missing behaviors, and requests human demonstrations on demand to acquire new skills. On two dual-arm laboratory tasks containing 20 and 31 ordered skill calls respectively, BioAgent achieved full-task success rates of 66% and 58%, respectively, under conditions with autonomous recovery enabled and 50 runs per task. In the second task, it reused 17 skills as-is, modified 2 existing implementations, and added 5 new skill types. Under conditions with recovery disabled and 50 autonomous trials per item, the success rate of the 25 atomic skills ranged from 84% to 100%, with 17 of them achieving 50/50.
Report timeline
- BioAgent: An embodied agent that autonomously acquires skills and expands capabilities for long-horizon laboratory protocols
BioAgent is an embodied agent for long-horizon laboratory protocols that acquires new skills by matching human-reviewed requirements with validated skills, selecting tool-based implementations for missing behaviors, and requesting human demonstrations as needed. On the second task, it reused 17 skills unchanged, modified 2 existing implementations, and added 5 new skill types; on two dual-arm laboratory tasks with 20 and 31 ordered skill invocations respectively, it achieved complete-task success rates of 66% and 58%, with each task run 50 times and autonomous recovery enabled.
arXiv cs.RO ·
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