Sajjad Haghzad

Papers

Total Citations

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About

Sajjad Haghzad is a researcher in robotics and computational optimization, with a primary focus on dynamic mobile robot path planning. His most cited work, "Optimization of dynamic mobile robot path planning based on evolutionary methods" (2015, 28 citations), introduces evolutionary algorithms to address the complex challenge of navigating robots through environments with moving obstacles. The key contribution lies in balancing path optimality, smoothness, and safety—critical factors for real-world autonomous navigation. By applying biologically inspired optimization techniques, Haghzad’s approach enables robots to adaptively replan routes in real time, improving both efficiency and collision avoidance. This work has been influential in the fields of swarm robotics and autonomous systems, providing a foundation for further research into adaptive path planning under uncertainty. Haghzad’s research bridges theoretical optimization and practical robotics, offering scalable solutions for dynamic environments. His contributions are particularly relevant for applications in warehouse automation, search-and-rescue missions, and autonomous vehicles, where reliable real-time navigation is essential. With a growing citation record, Haghzad continues to advance the intersection of evolutionary computation and mobile robotics.