xTechHumanoid
Supports autonomous humanoid robotics efforts through prizes and potential follow-on mission contracts.
xTechHumanoid is a two-phase prize competition operated by Army FUZE PIT to accelerate the development of humanoid robotic systems capable of performing military-relevant physical tasks. The program targets two distinct focus areas: Baseline Humanoid Systems designed for force augmentation in military environments, and Advanced Humanoid Subsystems that deliver enhanced sensors and autonomous capabilities. Up to ten finalists are selected in Phase 1, each receiving a $25,000 cash award. Phase 1 submissions closed on October 1, 2025, and ten finalists have already been selected and announced.
In Phase 2, up to five winners receive $75,000 each for baseline humanoid systems or $30,000 each for advanced subsystem solutions. The Phase 2 experimentation event runs from August through September 2026, with winners announced October 31, 2026. Total cash prizes across both phases reach $490,000. Winners also become eligible for potential follow-on contracts valued up to $1.25 million, though those awards are not guaranteed. Eligible participants include domestic and foreign businesses and nonprofits — government entities, organizations controlled by foreign adversaries, and entities based in Foreign Countries of Concern are excluded. Participants must obtain a CAGE (domestic) or NCAGE (foreign) business code.
Because the Phase 2 experimentation event has not yet occurred, proposals from companies with mature humanoid robotics systems should target the August–September 2026 event window. Competitors whose technologies have already been selected as Phase 1 finalists are actively progressing. Winning teams gain direct visibility with Army acquisition offices and access to the Army's innovation ecosystem through FUZE PIT, which regularly converts prize-competition results into procurement relationships.
1) Baseline Humanoid System — force augmentation for military tasks; 2) Advanced Humanoid Subsystems — enhanced sensors and autonomy.
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