Papers
13
Total Citations
145
H-Index
7
About
Tauhidul Alam is a robotics researcher whose work spans multi-robot coordination, autonomous navigation, privacy-preserving planning, and information gathering in resource-constrained environments. His research is particularly distinguished by its focus on minimalist and sensing-limited robots — systems equipped with little more than contact sensors and clocks — and on developing elegant algorithmic solutions that remain practical under real-world constraints. Alam's most-cited contribution, "Stochastic Multi-Robot Patrolling with Limited Visibility" (33 citations), exemplifies his interest in designing robust, unpredictable patrol strategies that resist adversarial exploitation. His work on privacy-preserving multi-robot coordination (25 citations) addresses a compelling and underexplored challenge: enabling robots to collaborate without fully exposing their individual goals or trajectories. His minimalist navigation research (17 citations) demonstrates that even severely constrained robots can achieve meaningful coverage through carefully designed dynamical systems. More recently, Alam has expanded into decentralized information gathering and hierarchical task-and-motion planning using deep reinforcement learning, signaling a broader ambition to tackle uncertainty and scalability in autonomous systems. With over 130 cumulative citations and a research trajectory that bridges theoretical rigor with practical robotics, Alam represents an emerging voice in the multi-robot systems community.
Research Focus
Key Achievements
Top Papers
- 1Stochastic Multi-Robot Patrolling with Limited Visibility33 citations · 2019
- 2Coordinated multi-robot planning while preserving individual privacy25 citations · 2019
- 3Minimalist Robot Navigation and Coverage Using a Dynamical System Approach17 citations · 2017
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- 6Decentralized Multi-Robot Information Gathering From Unknown Spatial Fields11 citations · 2023
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- 9Randomized Multi-Robot Patrolling with Unidirectional Visibility5 citations · 2024
- 10