Max Robotics — Global Service Robot Directory + US Certification

About

Mohamed Baslam is a researcher at the forefront of autonomous robotics and intelligent path planning, with a growing portfolio that bridges theoretical algorithms and real-world applications. His work centers on developing efficient navigation and coverage strategies for autonomous systems, particularly in complex and hazardous environments. A key contribution is his hybrid approach to path planning, which intelligently combines Dijkstra’s algorithm with A* search, enhanced by an optional adaptive threshold heuristic—a method that has already garnered 9 citations for its practical improvements in computational efficiency. Baslam’s research extends to multi-agent systems, as seen in his work on ant trajectory planning with collaborative computer vision, and to accessible technology, where he applies TinyML on Arduino Nano 33 BLE to assist disabled individuals. Notably, his 2017 paper on a Markov Decision Model for area coverage in autonomous demining robots addresses the critical challenge of exploring unknown, mine-contaminated environments, proposing a robust framework for optimal path planning. Through these contributions, Baslam demonstrates a commitment to advancing autonomous systems that are both intelligent and socially impactful.