Research Area

Structural Health Monitoring

Structural Health Monitoring (SHM) is an interdisciplinary domain that combines multiple disciplines, including computer vision, signal processing, sensor technology, data science, material science, civil, mechanical, and aerospace engineering. Its purpose is to assess the condition of civil or industrial structures like bridges, buildings, aircraft, and wind turbines. The main goal is to continuously monitor structural responses, enabling the evaluation of structural integrity and detection of any damages.

Our team is working on vision-based structural health monitoring techniques equipped with stereovision system. The research team is building an automatic, real-time, self-calibrating and in-house DIC software to measure the health of large structures.

Digital Image Correlation

DIC is widely used in experimental mechanics, material sciences, civil engineering, structural engineering, aerospace engineering, and so on for measuring full-field displacement, strain responses, material characteristics, and structural integrity.

We are developing an automated DIC software which can measure high order full-field deformation of a material.

Bio-inspired Micro Aerial Vehicle

Flapping videos.pptx

“According to all known laws of aviation, there is no way that a bee should be able to fly. Its wings are too small to get its fat little body off the ground. The bee, of course, flies anyway. Because bees don't care what humans think is impossible.”

Insects are the masters of flight. Their exceptional maneuverability, adaptability to wind currents, and light weight structure makes them an excellent choice of inspiration for developing smart and agile Micro Air Vehicles (MAVs). Notably, insects possess mechanosensors - sensors that can detect strain induced due to external aerodynamic forces, allowing them to maintain stable flight with through this sensory feedback.

Our team is exploring the materials that can both sense and function as actuators. The application of these materials aims to mimic the biological sensors in a way to replicate wind sensing abilities and the dynamic control of insects. Integrating these materials into the structure of MAVs not only enables the direct measurement of load for flight control but also eliminates the need for conventional control systems.

Smart Structures

Smart materials, particularly carbon nanotube (CNT)-enhanced fibre-reinforced polymers (FRPs), play a pivotal role in SHM. These materials inherently respond to mechanical stimuli, such as strain, deformation, or cracks, by exhibiting measurable changes in their electrical, thermal, or optical properties. When embedded into composite structures, CNTs enable self-sensing capabilities, allowing the material itself to act as a sensor.

This fusion of material intelligence and SHM technology forms the foundation of next-generation aerospace structures, where real-time, in-situ monitoring is essential for safety, performance, and mission-critical reliability.

Autonomous UAV Navigation

Autonomous navigation of unmanned aerial vehicles (UAVs) in GPS-enabled environments—such as disaster management, package delivery, and certain military operations—requires reliable onboard perception and planning to operate safely and efficiently.

Our team is working on a vision-based solution that replaces heavy and expensive LiDAR sensors with a stereo camera and deep learning models to achieve 3D perception, object detection, and path planning.

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