Research Projects Archives - Embedded and Multi-sensor Systems Lab (EMSLab)

Indoor UAV Navigation by Fusing IMU and UWB Wireless Sensors

changqiu — Wed, 07 Jul 2021 19:03:57 +0000

This projects aims at enabling unmanned aerial vehicles to navigate indoors without GPS by fusing sensors data from IMU and Ultra wide band wireless sensors.

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Non-GPS Multi-sensor Positioning/Mapping System for First-responders

changqiu — Wed, 07 Jul 2021 19:01:08 +0000

Emergency crew and first responders face significant challenges in exploring unknown areas and handling situations in complex environments that do not have GPS signals. This project developed a wearable system that integrates multiple sensors to enable first-responders and emergency crew to dynamically build an awareness of any unknown area including team members locations and environment […]

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Smart Helmet: Fusing Low-cost Single-beam Laser and IMU for Mining Workers Tracking

changqiu — Tue, 06 Jul 2021 02:18:34 +0000

A new LiDAR SLAM for Pedestrian (Helmet-mount) using 2D LiDAR sensor and IMU. IMU is used to perform Pedestrian Dead Reckoning to improve LiDAR SLAM on body-mounted platforms.

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Fusing Radar and inertial sensors for long-corridor indoor navigation

changqiu — Tue, 06 Jul 2021 02:18:14 +0000

Light Detection and Ranging (LiDAR) based Simultaneous Localization and Mapping (SLAM) systems are often used to map indoor areas and localize mobile systems. LiDAR scan matching performs poorly in environments without rich geometry, such as long hallways or large rooms. To address this limitation, a mm-wave fixed antenna array radar is used as a low-cost aid towards maintaining full pose information during these situations. Localization is performed using a scan matching algorithm that is developed through a correlative method.

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Autonomous Car Navigation using Visual/Inertial Sensor Fusion

changqiu — Tue, 06 Jul 2021 02:17:55 +0000

To enable autonomous car navigation in GPS-denied environments, this project developed a multi-state Kalman filter that fuses visual features and inertial sensors in a tightly-coupled integration mode. The fusion of visual and inertial modalities enjoys growing popularity due to miniaturization and affordability of the sensors which make them ideal backups to the Global Navigation Satellite Systems (GNSS) where the service is interrupted in urban areas.

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