Jugesh Sundram

Singapore University of Technology and Design, Toyota Motor Corporation (Belgium)

Papers

Total Citations

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About

Jugesh Sundram is a robotics researcher specializing in miniature robotic systems, multi-robot coordination, and visual localization under dynamic lighting conditions. His most influential work, "Development of a Miniature Robot for Multi-robot Occupancy Grid Mapping" (2018, 10 citations), introduces Orion—a compact 12×12 cm, 150-gram differential drive robot designed for Intelligent Surveillance and Reconnaissance (ISR) tasks. This contribution demonstrates Sundram’s focus on creating small-scale, agile platforms capable of collaborative mapping in constrained environments, a critical capability for search-and-rescue and security applications. In his more recent work, "Real-Time Outdoor Illumination Estimation for Camera Tracking in Indoor Environments" (2021, 3 citations), Sundram addresses the persistent challenge of dynamic lighting in visual robot localization. By proposing a method that estimates indoor scene appearance in real-time using reflectance maps and current outdoor illumination, he advances robust camera tracking for robots operating in spaces with variable natural light. Sundram’s research bridges hardware design and perception algorithms, offering practical solutions for autonomous navigation in complex, real-world settings. His work is particularly relevant for students and researchers interested in swarm robotics, SLAM under challenging conditions, and the integration of compact hardware with intelligent software.