Max Robotics — Global Service Robot Directory + US Certification

About

Minho Heo is a roboticist whose research centers on scaling robot manipulation to complex, real-world tasks. His most impactful contribution is the creation of **DROID**, a large-scale, in-the-wild robot manipulation dataset that has rapidly garnered over 100 citations. This dataset is a cornerstone for training robust, generalizable manipulation policies by providing diverse, high-quality data from unstructured environments. Heo also leads the **FurnitureBench** project, a reproducible real-world benchmark designed to push the boundaries of long-horizon, complex manipulation—specifically furniture assembly. This benchmark challenges robots with dexterous control, visual perception, and multi-step planning, bridging the gap between simple lab tasks and practical applications. By providing standardized, easy-to-reproduce evaluation protocols, Heo’s work enables rigorous comparison of reinforcement learning, imitation learning, and task-and-motion planning approaches. His efforts are instrumental in moving the field beyond simple behaviors toward capable, adaptable robots that can operate in the messy, unpredictable world.