Mohammad-Hashem Haghbayan
Papers
9
Total Citations
120
H-Index
5
About
Mohammad-Hashem Haghbayan is a robotics and autonomous systems researcher whose work spans swarm robotics, energy-efficient mobile robot control, collaborative navigation, and multi-UAV formation systems. His research addresses some of the most pressing challenges in modern robotics: enabling autonomous agents to perceive, navigate, and cooperate intelligently within complex real-world environments. Among his most influential contributions is a low-cost ultrasonic-based collision avoidance method for autonomous robots (2020, 52 citations), which demonstrates his commitment to practical, accessible solutions in robot perception. His comparative study of linear and nonlinear control methods for hierarchical UAV swarm formations (28 citations) has meaningfully advanced distributed multi-agent coordination. Haghbayan has also pioneered work in event-camera-based visual odometry and IMU fusion, reflecting his interest in next-generation sensor technologies for dynamic environments. His later research on DCP-SLAM introduces distributed collaborative mapping for energy-efficient swarm navigation, while his coordinated mechanical and computational resource management frameworks address critical battery-lifetime challenges in field robotics. Most recently, he has explored IoT communication optimization for swarm systems and energy-constrained reinforcement learning problems. Collectively, Haghbayan's portfolio — accumulating over 120 citations — represents a coherent vision of intelligent, efficient, and collaborative autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 7The Mountain Car Problem with a Dynamical and Finite Energy System2 citations · 2024
- 8Monocular visual odometry based on hybrid parameterization2 citations · 2020
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