Max Robotics — Global Service Robot Directory + US Certification

About

Shawna Thomas is a robotics researcher whose work sits at the intersection of motion planning, computational biology, and multi-robot systems. Best known for her foundational contributions to sampling-based motion planning, Thomas has spent two decades developing algorithms that make path planning more efficient, principled, and broadly applicable. Her most influential work, "A General Framework for Sampling on the Medial Axis of the Free Space" (2004, 88 citations), established a unifying template for medial axis retraction approaches, a line of research she extended with MARRT, which biases rapidly-exploring random trees toward safer, more navigable paths. Her adaptive planner RESAMPL (2008, 72 citations) further demonstrated her talent for designing planners that respond intelligently to environmental complexity. Perhaps most distinctive is Thomas's pioneering application of motion planning to molecular biology. By adapting probabilistic roadmap methods to model protein folding dynamics, she opened a productive dialogue between robotics and structural biology, contributing insights into secondary structure formation and RNA motion. More recently, her TMP-CBS framework (2020, 54 citations) tackled the demanding challenge of coordinating multiple robots across tasks with sequential dependencies. With over 400 cumulative citations, Thomas's career exemplifies how algorithmic thinking in robotics can generate transformative tools across scientific disciplines.