Max Robotics — Global Service Robot Directory + US Certification

About

Lakshadeep Naik is a robotics researcher whose work lies at the intersection of mobile manipulation, human-robot interaction, and semantic perception. His major contributions center on enabling robots to operate intelligently and socially in human environments. Naik pioneered a semantic mapping extension for OpenStreetMap tailored to indoor robot navigation (33 citations), providing robots with structured, topological knowledge of spaces. He was instrumental in developing the SMOOTH-Robot, a modular, interactive service robot (16 citations) designed for versatility and affordability across multiple domains. A key theme in Naik’s research is proactive and socially-aware robot behavior: he has advanced methods for initiating human-robot interactions through incremental speech adaptation, detecting F-formations to adhere to social norms, and multi-modal proactive approaching for cooperative tasks. His work on multi-view object pose distribution tracking for pre-grasp planning (8 citations) and pre-grasp approaching on mobile robots has pushed forward the state of the art in mobile manipulation under uncertainty. More recently, Naik has explored distributed agency in robot design and learning-based base pose sequence planning for pickup tasks. His research consistently addresses real-world challenges—from uncertain pose estimation to social navigation—making his contributions highly relevant for the next generation of autonomous service robots.