Papers
16
Total Citations
271
H-Index
10
About
Aufar Zakiev is a robotics researcher whose work bridges simulation, swarm intelligence, and real-world crisis response. His core contributions lie in developing automatic tools that transform 2D images and sensor data into realistic 3D environments for the Gazebo simulator—a foundational capability for testing navigation, mapping, and SLAM algorithms without costly physical trials. His most cited paper (54 citations) introduced a tool for constructing 3D solid models from grayscale images, while related works on occupancy grid mapping and octomap generation have further streamlined simulation workflows. Zakiev has also made notable strides in swarm robotics, clarifying terminology and classification in a widely referenced 2018 paper (35 citations). Demonstrating the practical impact of his work, he contributed to automating pandemic mitigation strategies (36 citations) and developed an RFID-based warehouse management system using heterogeneous robot teams. His research extends to emergency management, including an international collaboration for flood and landslide disaster information systems, and he has created browser-based monitoring tools using ROS and ReactJS. With over 200 total citations, Zakiev’s work is essential reading for anyone interested in robotic simulation, multi-robot systems, and deploying robots in safety-critical environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Automating pandemic mitigation36 citations · 2021
- 3Swarm Robotics: Remarks on Terminology and Classification35 citations · 2018
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- 6Tool for 3D Gazebo Map Construction from Arbitrary Images and Laser Scans18 citations · 2017
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- 9Online Monitoring and Visualization with ROS and ReactJS10 citations · 2021
- 10