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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At CMU's Biorobotics Lab and Red Whittaker's Field Robotics Center, Joshua developed GPU-accelerated MPPI controllers for off-road vehicles — earning CMU's DARPA RACER team one of three Phase 1 slots globally, placing Team Explorer 4th in the DARPA SubT Final, and contributing to RadPiper, a DoE-funded inspection robot deployed to former nuclear enrichment facilities. He co-founded an autonomous racing team as Chief Engineer — raising $120K to acquire a full-scale Dallara AV-21, writing the controls and planning stack that reached 138 mph, and producing code that raced on in overtaking competitions after he stepped away. At Field AI, he built the Federal defense subsidiary from scratch — winning the Army xTech Overwatch competition, landing multiple DoD contracts, and proving he could scale frontier autonomy into competitive military programs. He now architects autonomous UGV systems at Detroit Defense, completing the full arc from DARPA research to production deployment.
Joshua is a PhD candidate at the University of Rochester's Robotics and AI Laboratory, where his DARPA RACER research produced DiEASL — a differentiable motion planner adapting state lattice search to off-road terrain — while a parallel NASA grant explores dialogue-driven autonomy on the Astrobee free-flyer at NASA Ames. Before graduate school, he interned at JHU Applied Physics Lab on a prototype of NASA's Dragonfly Titan mission and at JPL on the NEOWISE comet survey, building a scientific foundation that sharpens his approach to sensor-limited, safety-critical systems in contested environments. He then served as an ORAU Fellow at Army Research Laboratory and Autonomy Engineer at Booz Allen Hamilton's Digital Battlespace Group, translating research into DoD deliverables and building sustained access across the defense acquisition ecosystem. He now brings that full stack — research depth, government relationships, and program credibility — to autonomous systems work at 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