George Konidaris Research Group

Brown University

Can robots autonomously learn abstract skills that enable fast, goal-directed planning across diverse tasks and environments? The Intelligent Robot Lab constructs high-level symbolic representations and abstraction hierarchies to enable planning, for example work on "From Skills to Symbols" and related projects. The lab develops hierarchical reinforcement learning and probabilistic learning methods to learn task-level skills and then composes them for long-horizon planning using projects such as "Autonomous Robot Skill Acquisition." Researchers integrate optimal control, planning, and learned skills to produce robust behavior under uncertainty in manipulation and navigation. The lab builds applied systems including robot motion-planning hardware and software prototypes described as "Robot Motion Planning on a Chip.