Farid Bounini

Papers

Total Citations

177

H-Index

About

Farid Bounini is a leading researcher in autonomous navigation and mobile robotics, with a primary focus on intelligent vehicle path planning and obstacle avoidance. His most impactful contribution is the development of a modified artificial potential field (APF) method for online path planning, detailed in his 2017 paper, which has garnered 177 citations. This work directly addresses a critical limitation of the standard APF approach—the local minima problem that can trap robots or vehicles in suboptimal positions—by introducing an innovative solution that enables real-time, efficient navigation in dynamic environments. Bounini’s research bridges theoretical algorithms and practical applications, enhancing the safety and reliability of autonomous systems. His contributions are widely recognized in the fields of robotics and intelligent transportation, influencing subsequent studies on collision avoidance and path optimization. Through his work, Bounini has established himself as a key figure in advancing the autonomy of mobile robots and intelligent vehicles, making his research essential for students and engineers developing next-generation navigation systems.