Tarem Ahmed
Papers
3
Total Citations
13
H-Index
3
About
Tarem Ahmed is a robotics researcher specializing in autonomous navigation, multi-robot coordination, and swarm intelligence. His work focuses on solving critical challenges in simultaneous localization and mapping (SLAM) and search-and-rescue operations using decentralized robotic systems. In his most cited work, "Sonar-based SLAM Using Occupancy Grid Mapping and Dead Reckoning" (6 citations), Ahmed developed a solution for indoor autonomous navigation by integrating sonar data with occupancy grid mapping, enabling a differential drive robot to construct environmental maps while tracking its relative position. He has made significant contributions to swarm robotics through innovative algorithms for multi-robot search. His "Multi-robot Search Algorithm using Timed Random Switching of Exploration Approaches" (4 citations) introduces a novel method where robots dynamically alternate between variable and fixed distance repulsion strategies to improve exploration efficiency. Ahmed further advanced the field with "A New Multi-Robot Search Algorithm Using Probabilistic Finite State Machine and Lennard-Jones Potential Function" (3 citations), which models robot interactions using molecular-inspired potential functions combined with probabilistic state transitions. His work demonstrates how bio-inspired and physics-based approaches can enhance the effectiveness of robotic swarms in time-critical missions such as disaster response, making him a notable contributor to the growing field of autonomous multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1Sonar-based SLAM Using Occupancy Grid Mapping and Dead Reckoning6 citations · 2018
- 2
- 3