Max Robotics — Global Service Robot Directory + US Certification

About

Manabu Nakanoya is an emerging researcher working at the intersection of robotics, machine learning, and networked systems, with a particular focus on cloud robotics, autonomous driving, and efficient sensory data transmission. His work addresses a critical challenge in modern robotics: how resource-constrained robots — from low-power drones to space and subterranean rovers — can intelligently compress and transmit high-bitrate sensory data, such as video and LiDAR streams, to remote compute servers without sacrificing task performance. Nakanoya's co-design framework for communication and machine inference represents a notable contribution, optimizing the interplay between data transmission and downstream AI decision-making in cloud robotics pipelines. His research on task-relevant representation learning further advances this agenda by ensuring that only mission-critical perceptual information is prioritized during transmission. Additionally, his work on personalized federated learning for autonomous vehicles demonstrates a sophisticated understanding of how fleets can collaboratively improve trajectory forecasting models across heterogeneous environments while preserving data privacy. Though early in his career, Nakanoya's publications have already garnered meaningful citations across multiple venues, signaling growing recognition within the robotics and machine learning communities.