Max Robotics — Global Service Robot Directory + US Certification

About

Dan Helmick is a leading roboticist whose work sits at the intersection of mobile manipulation, human-robot teaching, and real-world deployment. His most impactful contribution is the development of a mobile manipulation system capable of one-shot task learning: after a single demonstration in virtual reality, the robot can autonomously perform complex, multi-step tasks in real, unmodified homes—a breakthrough that earned his 2020 paper 21 citations. Helmick’s approach is grounded in rigorous, metrics-driven evaluation; he famously benchmarked his general-purpose system by having it autonomously grocery shop in a real, unmodified store, demonstrating robust performance in the wild. Beyond whole-body manipulation, he has advanced foundational algorithms for robot teams, including leader/follower behaviors for urban reconnaissance, and developed a direct semi-exhaustive search method for robust point cloud registration. His motion planning work, leveraging large-scale dynamic roadmaps, achieves reliable, sub-second planning for high-degree-of-freedom robots in changing environments. Through this combination of practical system building and algorithmic depth, Helmick is pushing mobile manipulation from the lab into the messy, unstructured world where it matters most.