Max Robotics — Global Service Robot Directory + US Certification

About

Manabu Saito’s research lies at the intersection of autonomous mobile robotics, human-robot interaction, and semantic perception, with a focus on enabling robots to operate intelligently in large-scale, unstructured environments. His most influential work, “Searching objects in large-scale indoor environments: A decision-theoretic approach” (40 citations), introduces a probabilistic framework that allows robots to efficiently locate task-relevant objects beyond their immediate sensor range—a critical capability for autonomous manipulation in real-world settings like homes or offices. Building on this, his paper “Semantic Object Search in Large-scale Indoor Environments” (14 citations) incorporates contextual knowledge to guide search strategies, reducing uncertainty and improving success rates. Saito also advances intuitive robot control: his work on view-based multi-touch gesture interfaces (10 citations) enables non-expert users to command furniture-manipulation robots through simple gestures, while his pedestrian detection system (4 citations) combines a laser range finder with an omni-view camera for safe outdoor navigation of personal mobility robots. Across these contributions, Saito demonstrates a consistent commitment to bridging perception, decision-making, and user-friendly design—making robots more autonomous, context-aware, and accessible for everyday assistance.