Mannan Saeed Muhammad
Papers
6
Total Citations
167
H-Index
5
About
Mannan Saeed Muhammad is a robotics and artificial intelligence researcher whose work centers on autonomous robot navigation, deep reinforcement learning, and human-robot interaction. He has made significant contributions to the field of socially compliant robot navigation, developing innovative approaches that enable robots to move safely and intelligently through complex, crowded environments by modeling and predicting human behavior. His most influential work, "Socially Compliant Robot Navigation in Crowded Environment by Human Behavior Resemblance Using Deep Reinforcement Learning" (2021), has garnered 86 citations, establishing him as a notable voice in social robotics. Building on this foundation, he introduced concepts such as dynamic warning zones and memory-based crowd-awareness to further enhance robot decision-making in dynamic spaces, accumulating an additional 53 citations across follow-up studies. His research portfolio also extends to aerial robotics, where his adaptive bidirectional A* algorithm addresses path planning challenges for drones, and to 3D shape reconstruction for robotic applications. With roots in human tracking and computer vision dating back to 2013, Muhammad has demonstrated a sustained commitment to bridging perception, learning, and autonomous behavior. His growing citation record reflects an expanding influence on how future service and social robots will navigate our shared physical world.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Memory-based crowd-aware robot navigation using deep reinforcement learning22 citations · 2022
- 4ABA*–Adaptive Bidirectional A* Algorithm for Aerial Robot Path Planning18 citations · 2023
- 5Human tracking by a mobile robot using 3D features7 citations · 2013
- 6