Max Robotics — Global Service Robot Directory + US Certification

About

Ahmed Oultiligh is a robotics researcher whose work focuses on intelligent path planning and obstacle avoidance for autonomous mobile robots. His core research integrates swarm intelligence algorithms, metaheuristic optimization, and fuzzy logic control to enable robots to navigate safely and efficiently in uncertain, obstacle-rich environments. Oultiligh has made notable contributions by proposing novel hybrid approaches that combine algorithms such as Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) to improve trajectory planning under static and dynamic constraints. His 2023 paper on an improved elephant herding optimization for mobile robot path planning, along with his earlier work on hybrid PSO-GWO and fuzzy controllers, each have garnered 5 citations, reflecting steady interest from the robotics and optimization communities. His 2020 studies on fuzzy logic-based obstacle avoidance for unicycle robots further demonstrate his commitment to practical, real-time navigation solutions. Oultiligh’s research is particularly valuable for students and engineers seeking to understand how bio-inspired computation can be applied to autonomous systems, bridging the gap between theoretical optimization and real-world robotic control.