Utayba Mohammad
Papers
2
Total Citations
5
H-Index
2
About
Utayba Mohammad's research focuses on advancing autonomous navigation for mobile robots, with particular emphasis on path planning and obstacle avoidance for differential drive vehicles. His work addresses critical challenges in real-world robotic navigation, especially in complex environments where simple reactive algorithms fall short. In his highly cited 2012 paper "Navigating with VFH: a strategy to avoid traps," Mohammad identified limitations in the Vector Field Histogram (VFH) algorithm when applied to increasingly complex IGVC Navigation Challenge courses, proposing enhanced strategies to prevent robots from becoming trapped. Building on this, his 2013 work "A new trajectory-based path planning approach for differential drive vehicles" introduced an innovative local path planning algorithm that integrates vehicle dynamics models directly into the decision-making process. By formulating the problem in trajectory space rather than traditional configuration space, Mohammad's approach enables smoother, more accurate path contouring during autonomous operation. Though his citation counts are modest, his contributions represent important incremental advances in practical robot navigation, demonstrating how incorporating vehicle-specific dynamics can significantly improve real-world autonomous performance.
Research Focus
Key Achievements
Top Papers
- 1Navigating with VFH: a strategy to avoid traps3 citations · 2012
- 2