Built by engineers who've spent the last decade doing the work — DARPA programs, standing up defense subsidiaries, competing for and winning DoD contracts. We help defense programs and tech companies close the gap from R&D to fielded capability.
From concept to fielded capability — we bring deep technical expertise and operational understanding to every engagement.
Architecture, integration, and fielding of UGVs and autonomous platforms for defense programs — from DARPA-funded R&D through production DoD deployments and A-Kit retrofit programs.
GPU-accelerated perception, sensor fusion, and closed-loop AI for platforms operating in off-road, GPS-denied, and contested environments.
SBIR/STTR and OTA capture, DARPA transition planning, RFI/RFP development, and direct engagement with DoD program offices and prime contractors.
Standing up field testing infrastructure, autonomy system validation, and cross-functional team leadership for complex defense technology programs.
Iokath is a defense autonomy consulting firm founded by engineers with direct, recent experience inside DoD programs. Our founders built Field AI's Federal defense subsidiary from scratch, led teams that won the Army xTech Overwatch competition, contributed to multiple DoD contract awards, and now architect autonomous UGV systems at Detroit Defense.
We draw on firsthand depth from DARPA RACER, DARPA SubT, Army Research Laboratory, and Booz Allen Hamilton's Digital Battlespace Group. When we advise on fielding — we've done the fielding.
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Joshua's career spans robotics research and defense deployment. At CMU, he developed GPU-accelerated MPPI motion planners for off-road vehicles, led the university's DARPA RACER team (one of three Phase 1 selectees nationwide), placed 4th globally on DARPA SubT's Team Explorer, and contributed to RadPiper — a DoE-funded pipe robot deployed to inspect former uranium enrichment facilities. At Field AI, he built the Federal defense subsidiary from scratch — winning the Army xTech Overwatch competition and landing multiple DoD contracts along the way. He now architects autonomous UGV systems at Detroit Defense.
Joshua is a PhD candidate at the University of Rochester's Robotics and AI Laboratory, where his research bridges off-road autonomous navigation and human-robot teaming. His DARPA RACER work produced DiEASL, a differentiable motion planner that adapts state lattice search to terrain; a parallel NASA grant explores dialogue-based robot planning with hardware on the Astrobee free-flyer at NASA Ames. Before graduate school, he interned twice at JHU Applied Physics Lab — including on a prototype of NASA's Dragonfly Titan mission — and at NASA JPL on the NEOWISE comet survey, giving him an unusual scientific foundation for a defense engineer. He's since served as an ORAU Fellow at Army Research Laboratory and Autonomy Engineer at Booz Allen Hamilton's Digital Battlespace Group, and now brings that depth to Detroit Defense.
Whether you have a defined program, an RFI to respond to, or an early-stage problem — we're happy to talk through how we can help.
contact@iokath.ai