Max Robotics — Global Service Robot Directory + US Certification

About

Khawar Naheem is a robotics researcher whose work centers on fall detection for elderly care and the development of novel lighter-than-air indoor robots. His most impactful contribution is a deep neural network–based double-check method for fall detection, which fuses data from an IMU-L sensor and an RGB camera to achieve 100% accuracy—a significant leap over existing systems that suffer from missed detections or false alarms. This work, published in 2021, has garnered 42 citations, underscoring its influence in assistive technology. Naheem is also a pioneer in lighter-than-air (LTA) robot navigation, where he has addressed the challenge of safe, collision-free indoor flight using ultra-wideband (UWB) positioning systems. His research demonstrates the feasibility of UWB for tracking LTA robots and introduces the LAIDR platform—a robotics research platform designed for interactive entertainment applications. With an adaptive propulsion mechanism that minimizes the number of propulsion units, LAIDR enables variable in-mission configurations, pushing the boundaries of human-robot interaction. Naheem’s work on real-time flight control algorithms further advances the practical deployment of these safe, long-flight-time robots in user-centered environments.