Ke Luo

Papers

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About

Ke Luo is an emerging researcher whose work sits at the intersection of robotics, edge computing, and autonomous systems. His research primarily focuses on advancing Simultaneous Localization and Mapping (SLAM) technologies, particularly in the challenging context of multi-robot collaboration, where limited on-device computational resources have traditionally hindered real-time performance. Luo's most notable contribution, *ColaSLAM* (2021), proposes a collaborative laser SLAM framework that leverages edge computing to overcome the resource constraints inherent in multi-robot systems — a paper that has garnered 13 citations and established him as a meaningful voice in the field. Building on this theme, his complementary work on edge-computing-accelerated multi-robot SLAM further reinforces his commitment to making distributed robotic intelligence both practical and scalable. More recently, Luo has expanded his scope into human-machine interaction, demonstrated through *DoodBot*, an edge-assisted manipulator system capable of playing chess in non-ideal real-world environments — showcasing his interest in bridging autonomous robotic control with everyday human contexts. Across his portfolio, Luo consistently addresses the gap between theoretical robotics capability and real-world deployment constraints, positioning himself as a researcher with strong applied instincts and growing influence in intelligent robotic systems.