Max Robotics — Global Service Robot Directory + US Certification

About

Marc Eisoldt is a robotics and embedded systems researcher whose work sits at the intersection of reconfigurable computing, autonomous navigation, and hardware acceleration. His primary research focuses on enabling computationally intensive robotics algorithms — particularly Simultaneous Localization and Mapping (SLAM) — to run efficiently on resource-constrained embedded platforms using FPGAs and reconfigurable Systems-on-Chip (SoCs). Eisoldt's most notable contributions include the development of ReconfROS, a framework that bridges the widely adopted Robot Operating System (ROS) with FPGA-based hardware acceleration, allowing robotics developers to integrate custom hardware directly into established software ecosystems. His work on HATSDF SLAM represents a significant achievement in hardware-accelerated 3D LiDAR-based SLAM using Truncated Signed Distance Fields, delivering energy-efficient, real-time mapping suitable for embedded robotics platforms. These contributions collectively address one of autonomous robotics' core challenges: achieving high-performance localization and mapping without the power budgets of full desktop systems. With papers accumulating over 50 citations across publications from 2021 to 2023, Eisoldt's research has garnered meaningful attention within the robotics and reconfigurable computing communities, reflecting the growing demand for deployable, energy-efficient autonomous systems in real-world environments.