Alireza Nakhaei

Centre National de la Recherche Scientifique, Université Toulouse III - Paul Sabatier

Papers

Total Citations

185

H-Index

About

Alireza Nakhaei is a leading researcher in humanoid robotics, specializing in whole-body motion planning, dynamic walking, and vision-based autonomous navigation. His work addresses one of the most challenging problems in robotics: enabling humanoid robots to move and manipulate objects safely and efficiently in complex, unstructured environments. Nakhaei’s most influential contribution is his integrated approach to motion planning, which combines randomized algorithms with task constraints to generate collision-free, statically stable walking and manipulation motions. His seminal 2013 paper, with 80 citations, introduced a general method for planning whole-body walking motions, while his 2009 work (54 citations) advanced the field by integrating collision avoidance into task planning using an RRT-connect-inspired algorithm. Nakhaei also pioneered the concept of “documented” objects—items that carry manipulation instructions—allowing robots to autonomously handle unfamiliar objects. His 2008 paper on vision-based motion planning (30 citations) further demonstrated real-time 3D environment modeling for non-static settings. With over 185 total citations across his key works, Nakhaei’s research has laid critical groundwork for autonomous humanoid robots operating in human-centered environments, bridging perception, planning, and control.