Research Activities

Dr Tarek Taha currently leads the Robotics Lab at Dubai Future Foundation. He has more than 15 years of experience in the fields of robotics, autonomous systems and artificial intelligence while working for both, industry and academia.

Having worked extensively in the robotics, autonomous systems and artificial intelligence domains, I have developed great interest in advancing the state of robotics and autonomous systems to enable their deployment in practical applications.

Search and Rescue

Robotic Search and Rescue (RSAR) is a challenging yet promising technology area with the potential of high-impact practical deployment in real-world search and rescue disasters scenarios. Response time in a disaster environments is considered a key factor that requires a careful balance between rapid and safe intervention. SAR response should be fast and rapid in order to maximize the number of detected survivors/victims and locate all sources of danger in a timely manner. Appropriate disaster response should be organized and synchronized in order to save as many victims as possible, the primary objective in search and rescue operations. In general, responders have approximately 48 hours to find trapped survivors, otherwise the likelihood of finding victims alive drops substantially. Moreover, the conditions of SAR sites are usually hazardous making the SAR team more vulnerable, forced to operate in an unstructured environment with limited access to medical supplies, power sources, and other essential tools and utilities.

The research work conducted mainly focuses on:
    • Exploring indoor environment in order to identify and locate victims using multi-sensors (e.g., electro-optical,thermal, wireless, stereo imaging etc.)
    • Coordinating a team of robots and humans during search and rescue missions
    • Semantic environment mapping that labels hazards and ranks them
UAV based victim Localization
@article{goian2019victim,
    title={Victim localization in USAR scenario exploiting multi-layer mapping structure},
    author={Goian, Abdulrahman and Ashour, Reem and Ahmad, Ubaid and Taha, Tarek and Almoosa, Nawaf and Seneviratne,
    Lakmal}, journal={Remote Sensing},
    volume={11},
    number={22},
    pages={2704},
    year={2019},
    publisher={Multidisciplinary Digital Publishing Institute}
}
Exploration using Adaptive Grid Sampling
@article{almadhoun2019guided,
    title={Guided next best view for 3D reconstruction of large complex structures},
    author={Almadhoun, Randa and Abduldayem, Abdullah and Taha, Tarek and Seneviratne, Lakmal and Zweiri, Yahya},
    journal={Remote Sensing},
    volume={11},
    number={20},
    pages={2440},
    year={2019},
    publisher={Multidisciplinary Digital Publishing Institute}
}
Semantic Risk 3D Mapping
Exploration for Semantic 3D Mapping

Unmanned Aerial Vehicles (UAVs)

Dual UAV collaborative transportation
Multi-UAV co-ordinated payload transport
UAV payload transportation via RTDP
Energy Estimation and distribution
Dual UAV payload transportation using RTDP
Site Inspection Drone
UAV wireless charging and tethering
Next Best View (NBV) with profiling

Simultaneous Localization and Mapping (SLAM)<

This work focused on educing SLAM position estimation error by utilizing modern deep learning techniques and semantic scene understanding for a richer feature extraction.

Human Robot Interaction (HRI) in Assistive Robotics

The work focused on utilizing reinforcement learning to predict intentions during HRI for assistive robotics applications.

Intention prediction - wheelchair navigation
Intention prediction - wheelchair navigation

Other Activities

Strain sensor control

Robot control using flexible strain sensor from tissue paper

Robot Manipulation

Robot object grasping

Indoor UAV Swarms

Swarm formation - 5 Drones - GPS Denied

Haptics Teleoperation

Haptic based UAV Teleoperation
Autonomous Indoor Navigation
Semantic 3D mapping
3D Mapping with Image snapshots

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